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About Moative

Moative, an Applied AI Services company, designs AI roadmaps, builds co-pilots and predictive AI solutions for companies in energy, utilities, packaging, commerce, and other primary industries. Through Moative Labs, we aspire to build micro-products and launch AI startups in vertical markets.

Our Past: We have built and sold two companies, one of which was an AI company. Our founders and leaders are Math PhDs, Ivy League University Alumni, Ex-Googlers, and successful entrepreneurs.

Work you’ll do

As a Junior ML/ AI Engineer, you will help design and develop intelligent software to solve business problems. You will collaborate with senior ML engineers, data scientists and domain experts to incorporate ML and AI technologies into existing or new workflows. You’ll analyze new opportunities and ideas. You’ll train and evaluate ML models, conduct experiments, help develop PoCs and prototypes.

Responsibilities

• Designing, training, improving & launching machine learning models using tools such as XGBoost, Tensorflow, PyTorch.
• Contribute directly to the improvement of the way we evaluate and monitor model and system performances.
• Proposing and implementing ideas that directly impact our operational and strategic metrics.

Who you are

You are an engineer who is passionate about using AL/ML to improve processes, products and delight customers. You have experience working with less than clean data, developing and tweaking ML models, and are interested deeply in getting these models into production as cost effectively as possible. You thrive on taking initiatives, are very comfortable with ambiguity and can passionately defend your decisions.

Requirements and skills

• 3+ years of experience in programming languages such as Python, PySpark, or Scala.
• Proficient knowledge of cloud platforms (e.g., AWS, Azure, GCP) and containerization, DevOps (Docker, Kubernetes), 
• Beginner level knowledge of MLOps practices and platforms like MLflow.
• Strong understanding of ML algorithms and frameworks (e.g., TensorFlow, PyTorch).
• Broad understanding of data structures, data engineering, statistical methodologies and machine learning models.

Working at Moative

Moative is a young company, but we believe strongly in thinking long-term, while acting with urgency. Our ethos is rooted in innovation, efficiency and high-quality outcomes. We believe the future of work is AI-augmented and boundary less. Here are some of our guiding principles:

• Think in decades. Act in hours. As an independent company, our moat is time. While our decisions are for the long-term horizon, our execution will be fast – measured in hours and days, not weeks and months.
• Own the canvas. Throw yourself in to build, fix or improve – anything that isn’t done right, irrespective of who did it. Be selfish about improving across the organization – because once the rot sets in, we waste years in surgery and recovery.
• Use data or don’t use data. Use data where you ought to but not as a ‘cover-my-back’ political tool. Be capable of making decisions with partial or limited data. Get better at intuition and pattern-matching. Whichever way you go, be mostly right about it.
• Avoid work about work. Process creeps on purpose, unless we constantly question it. We are deliberate about committing to rituals that take time away from the actual work. We truly believe that a meeting that could be an email, should be an email and you don’t need a person with the highest title to say that loud.
• High revenue per person. We work backwards from this metric. Our default is to automate instead of hiring. We multi-skill our people to own more outcomes than hiring someone who has less to do. We don’t like squatting and hoarding that comes in the form of hiring for growth. High revenue per person comes from high quality work from everyone. We demand it.

If this role and our work is of interest to you, please apply here. We encourage you to apply even if you believe you do not meet all the requirements listed above.  

That said, you should demonstrate that you are in the 90th percentile or above. This may mean that you have studied in top-notch institutions, won competitions that are intellectually demanding, built something of your own, or rated as an outstanding performer by your current or previous employers. 

The position is based out of Chennai. Our work currently involves significant in-person collaboration and we expect you to be present in the city. We intend to move to a hybrid model in a few months time.

Key Responsibilities

• Design, develop, and optimize data pipelines using Apache Spark to process large volumes of structured and unstructured data.
• Write efficient and maintainable code in Scala and Python for data extraction, transformation, and loading (ETL) operations.
• Collaborate with cross-functional teams to define data engineering solutions to support analytics and machine learning initiatives.
• Implement and maintain data lake and warehouse solutions using cloud platforms (e.g., AWS, GCP, Azure).
• Ensure data workflows and distributed systems' performance, scalability, and reliability.
• Perform data quality assessments, implement monitoring, and improve data governance practices.
• Assist in migrating and refactoring legacy data systems into modern distributed data processing platforms.
• Provide technical leadership and mentorship to junior engineers and contribute to best practices in coding, testing, and deployment.
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Qualifications

• Bachelor's or Master’s degree in Computer Science, Engineering, or a related field.
• 6+ years of hands-on experience in data engineering, with strong skills in Apache Spark, Scala, and Python.
• Experience with distributed data processing frameworks and real-time data processing.
• Strong experience with big data technologies such as Hadoop, Hive, and Kafka.
• Proficient with relational databases (SQL, PostgreSQL, MySQL) and NoSQL databases (Cassandra, HBase, MongoDB). 
• Knowledge of CI/CD pipelines and DevOps practices for deploying data workflows.
• Strong problem-solving skills and experience with optimizing large-scale data systems.
• Excellent communication and collaboration skills.
• Experience with orchestration tools like Airflow
• Experience with containerization and orchestration (e.g., Docker, Kubernetes)

Key Responsibilities

• Design, develop, and optimize data pipelines using Apache Spark to process large volumes of structured and unstructured data.
• Write efficient and maintainable code in Scala and Python for data extraction, transformation, and loading (ETL) operations.
• Collaborate with cross-functional teams to define data engineering solutions to support analytics and machine learning initiatives.
• Implement and maintain data lake and warehouse solutions using cloud platforms (e.g., AWS, GCP, Azure).
• Ensure data workflows and distributed systems' performance, scalability, and reliability.
• Perform data quality assessments, implement monitoring, and improve data governance practices.
• Assist in migrating and refactoring legacy data systems into modern distributed data processing platforms.
• Provide technical leadership and mentorship to junior engineers and contribute to best practices in coding, testing, and deployment.

Qualifications

• Bachelor's or Master’s degree in Computer Science, Engineering, or a related field.
• 8+ years of hands-on experience in data engineering, with strong skills in Apache Spark, Scala, and Python.
• Experience with distributed data processing frameworks and real-time data processing.
• Strong experience with big data technologies such as Hadoop, Hive, and Kafka.
• Proficient with relational databases (SQL, PostgreSQL, MySQL) and NoSQL databases (Cassandra, HBase, MongoDB). 
• Knowledge of CI/CD pipelines and DevOps practices for deploying data workflows.
• Strong problem-solving skills and experience with optimizing large-scale data systems.
• Excellent communication and collaboration skills.
• Experience with orchestration tools like Airflow
• Experience with containerization and orchestration (e.g., Docker, Kubernetes)

The Sr. Analytics Engineer would provide technical expertise in needs identification, data modeling, data movement, and transformation mapping (source to target), automation and testing strategies, translating business needs into technical solutions with adherence to established data guidelines and approaches from a business unit or project perspective.

Understands and leverages best-fit technologies (e.g., traditional star schema structures, cloud, Hadoop, NoSQL, etc.) and approaches to address business and environmental challenges.

Provides data understanding and coordinates data-related activities with other data management groups such as master data management, data governance, and metadata management.

Actively participates with other consultants in problem-solving and approach development.

Responsibilities :

Provide a consultative approach with business users, asking questions to understand the business need and deriving the data flow, conceptual, logical, and physical data models based on those needs.

Perform data analysis to validate data models and to confirm the ability to meet business needs.

Assist with and support setting the data architecture direction, ensuring data architecture deliverables are developed, ensuring compliance to standards and guidelines, implementing the data architecture, and supporting technical developers at a project or business unit level.

Coordinate and consult with the Data Architect, project manager, client business staff, client technical staff and project developers in data architecture best practices and anything else that is data related at the project or business unit levels.

Work closely with Business Analysts and Solution Architects to design the data model satisfying the business needs and adhering to Enterprise Architecture.

Coordinate with Data Architects, Program Managers and participate in recurring meetings.

Help and mentor team members to understand the data model and subject areas.

Ensure that the team adheres to best practices and guidelines.

Requirements :

- Strong working knowledge of at least 3 years of Spark, Java/Scala/Pyspark, Kafka, Git, Unix / Linux, and ETL pipeline designing.

- Experience with Spark optimization/tuning/resource allocations

- Excellent understanding of IN memory distributed computing frameworks like Spark and its parameter tuning, writing optimized workflow sequences.

- Experience of relational databases (e.g., PostgreSQL, MySQL) and NoSQL databases (e.g., Redshift, Bigquery, Cassandra, etc).

- Familiarity with Docker, Kubernetes, Azure Data Lake/Blob storage, AWS S3, Google Cloud storage, etc.

- Have a deep understanding of the various stacks and components of the Big Data ecosystem.

- Hands-on experience with Python is a huge plus

Skills Required:

- 4+ years of technical experience in a developer role

- Strong proficiency with Core Java

- Database experience preferably with DB2, Sybase, or Oracle

- Complete SDLC process and Agile Methodology (Scrum)

- Strong oral and written communication skills

- Excellent interpersonal skills and professional approach

- Bachelor’s degree in Computer Science, MIS, or other technology/engineering discipline

Skill Desired:

-Strong proficiency with Scala on Spark

- Previous experience in front office and back office reports

- Strong understanding Order Life Cycle management from Equities or Listed derivatives perspective

- Previous experience in Trade Surveillance or working with data from the order lifecycle

- Good to have knowledge on Hadoop Technologies

- High quality software architecture and design methodologies and patterns

- Work experience as level-3 support for applications

- Layered Architecture, Component based Architecture

- XML-based technologies

- Unix OS, Scripting, Python or Perl

- Experience in development on other application types (Web applications, batch, or streaming)

• Architectural Leadership:
• Design and architect robust, scalable, and high-performance Hadoop solutions.
• Define and implement data architecture strategies, standards, and processes.
• Collaborate with senior leadership to align data strategies with business goals.
• Technical Expertise:
• Develop and maintain complex data processing systems using Hadoop and its ecosystem (HDFS, YARN, MapReduce, Hive, HBase, Pig, etc.).
• Ensure optimal performance and scalability of Hadoop clusters.
• Oversee the integration of Hadoop solutions with existing data systems and third-party applications.
• Strategic Planning:
• Develop long-term plans for data architecture, considering emerging technologies and future trends.
• Evaluate and recommend new technologies and tools to enhance the Hadoop ecosystem.
• Lead the adoption of big data best practices and methodologies.
• Team Leadership and Collaboration:
• Mentor and guide data engineers and developers, fostering a culture of continuous improvement.
• Work closely with data scientists, analysts, and other stakeholders to understand requirements and deliver high-quality solutions.
• Ensure effective communication and collaboration across all teams involved in data projects.
• Project Management:
• Lead large-scale data projects from inception to completion, ensuring timely delivery and high quality.
• Manage project resources, budgets, and timelines effectively.
• Monitor project progress and address any issues or risks promptly.
• Data Governance and Security:
• Implement robust data governance policies and procedures to ensure data quality and compliance.
• Ensure data security and privacy by implementing appropriate measures and controls.
• Conduct regular audits and reviews of data systems to ensure compliance with industry standards and regulations.

About the role

As a full-stack engineer, you’ll feel at home if you are hands-on, grounded, opinionated and passionate about building things using technology. Our tech stack ranges widely with language ecosystems like Typescript, Java, Scala, Golang, Kotlin, Elixir, Python, .Net, Nodejs and even Rust.

This role is ideal for those looking to have a large impact and a huge scope for growth while still being hands-on with technology. We aim to allow growth without becoming “post-technical”. We are extremely selective with our consultants and are able to run our teams with fewer levels of management. You won’t find a BA or iteration manager here! We work in small pizza teams of 2-5 people where a well-founded argument holds more weight than the years of experience. You will have the opportunity to work with clients across domains like retail, banking, publishing, education, ad tech and more where you will take ownership of developing software solutions that are purpose-built to solve our clients’ unique business and technical needs.

Responsibilities

• Produce high-quality code that allows us to put solutions into production.
• Utilize DevOps tools and practices to build and deploy software.
• Collaborate with Data Scientists and Engineers to deliver production-quality AI and Machine Learning systems.
• Build frameworks and supporting tooling for data ingestion from a complex variety of sources. Work in short sprints to deliver working software with clear deliverables and client-led deadlines.
• Willingness to be a polyglot developer and learn multiple technologies.

Skills you’ll need

• A maker’s mindset. To be resourceful and have the ability to do things that have no instructions.
• Extensive experience (at least 10 years) as a Software Engineer.
• Deep understanding of programming fundamentals and expertise with at least one programming language (functional or object-oriented).
• A nuanced and rich understanding of code quality, maintainability and practices like Test Driven Development.
• Experience with one or more source control and build toolchains.
• Working knowledge of CI/CD will be an added advantage.
• Understanding of web APIs, contracts and communication protocols.
• Understanding of Cloud platforms, infra-automation/DevOps, IaC/GitOps/Containers, design and development of large data platforms.

What will you experience in terms of culture at Sahaj?

• A culture of trust, respect and transparency
• Opportunity to collaborate with some of the finest minds in the industry
• Work across multiple domains

What are the benefits of being at Sahaj?

• Unlimited leaves
• Life Insurance & Private Health insurance paid by Sahaj
• Stock options
• No hierarchy
• Open Salaries

About this roleWe are seeking an experienced MongoDB Developer/DBA who will be

responsible for maintaining MongoDB databases while optimizing performance, security, and

the availability of MongoDB clusters. As a key member of our team, you’ll play a crucial role in

ensuring our data infrastructure runs smoothly.

You'll have the following responsibilities

 Maintain and Configure MongoDB Instances - Responsible for build, design, deploy,

maintain, and lead the MongoDB Atlas infrastructure. Keep clear documentation of the

database setup and architecture.

 Ownership of governance, defining and enforcing policies in MongoDB Atlas.Provide

consultancy in drawing the design and infrastructure (MongoDB Atlas) for use case.

 Service and Governance wrap will be in place to restrict over provisioning for server size,

number of clusters per project and scaling through MongoDB Atlas

 Gathering and documenting detailed business requirements applicable to the data

layer.Responsible for designing, configuring and managing MongoDB on Atlas.

 Design, develop, test, document, and deploy high-quality technical solutions on the

MongoDB Atlas platform based on industry best practices to solve business needs.

Resolves technical issues raised by the team and/or customer and manages escalations as

required.

 Migrate data from on-premise MongoDB and RDBMS to MongoDB AtlasCommunicate

and collaborate with other technical resources and customers in providing timely updates

on status of deliverables, shedding light on technical issues, and obtaining buy-in on

creative solutions.

 Write procedures for backup and disaster recovery.

You'll have the following skills & experience

 Excellent analytical, diagnostic skills, and problem-solving skills

 Should understand the Database concept and develop expertise in designing and

developing NoSQL databases such as MongoDB

 MongoDB query operation, import and export operation in database

 Experience in ETL methodology for performing Data Migration, Extraction,

Transformation, Data Profiling and Loading

 Migrating database by ETL, migrating database by manual process and designing,

development, implementation

 General networking skills, especially in the context of a public cloud (e.g. AWS – VPC,

subnets, routing tables, nat / internet gateways, dns, security groups)

 Experience using Terraform as an IaC tool for setting up infrastructure on AWS

CloudPerforming database backups and recovery

 Competence in at least one of the following languages (in no particular order): Java, C++,

C#, Python, Node.js (JavaScript), Ruby, Perl, Scala, Go

 Excellent communication skills, often being able to compromise but draw out risks and

constraints associated with solutions. Be able to work independently and collaborate with

other teams

 Proficiency in configuring schema and MongoDB data modeling.

 Strong understanding of SQL and NoSQL databases.

 Comfortable with MongoDB syntax.

 Experience with database security management.

 Performance Optimization - Ensure databases achieve maximum performance and

availability. Design effective indexing strategies.

Publicis Sapient Overview:

The Senior Associate People Senior Associate L1 in Data Engineering, you will translate client requirements into technical design, and implement components for data engineering solution. Utilize deep understanding of data integration and big data design principles in creating custom solutions or implementing package solutions. You will independently drive design discussions to insure the necessary health of the overall solution 

.

Job Summary:

As Senior Associate L2 in Data Engineering, you will translate client requirements into technical design, and implement components for data engineering solution. Utilize deep understanding of data integration and big data design principles in creating custom solutions or implementing package solutions. You will independently drive design discussions to insure the necessary health of the overall solution

The role requires a hands-on technologist who has strong programming background like Java / Scala / Python, should have experience in Data Ingestion, Integration and data Wrangling, Computation, Analytics pipelines and exposure to Hadoop ecosystem components. You are also required to have hands-on knowledge on at least one of AWS, GCP, Azure cloud platforms.

Role & Responsibilities:

Your role is focused on Design, Development and delivery of solutions involving:

• Data Integration, Processing & Governance

• Data Storage and Computation Frameworks, Performance Optimizations

• Analytics & Visualizations

• Infrastructure & Cloud Computing

• Data Management Platforms

• Implement scalable architectural models for data processing and storage

• Build functionality for data ingestion from multiple heterogeneous sources in batch & real-time mode

• Build functionality for data analytics, search and aggregation

Experience Guidelines:

Mandatory Experience and Competencies:

# Competency

1.Overall 5+ years of IT experience with 3+ years in Data related technologies

2.Minimum 2.5 years of experience in Big Data technologies and working exposure in at least one cloud platform on related data services (AWS / Azure / GCP)

3.Hands-on experience with the Hadoop stack – HDFS, sqoop, kafka, Pulsar, NiFi, Spark, Spark Streaming, Flink, Storm, hive, oozie, airflow and other components required in building end to end data pipeline.

4.Strong experience in at least of the programming language Java, Scala, Python. Java preferable

5.Hands-on working knowledge of NoSQL and MPP data platforms like Hbase, MongoDb, Cassandra, AWS Redshift, Azure SQLDW, GCP BigQuery etc

6.Well-versed and working knowledge with data platform related services on at least 1 cloud platform, IAM and data security

Preferred Experience and Knowledge (Good to Have):

# Competency

1.Good knowledge of traditional ETL tools (Informatica, Talend, etc) and database technologies (Oracle, MySQL, SQL Server, Postgres) with hands on experience

2.Knowledge on data governance processes (security, lineage, catalog) and tools like Collibra, Alation etc

3.Knowledge on distributed messaging frameworks like ActiveMQ / RabbiMQ / Solace, search & indexing and Micro services architectures

4.Performance tuning and optimization of data pipelines

5.CI/CD – Infra provisioning on cloud, auto build & deployment pipelines, code quality

6.Cloud data specialty and other related Big data technology certifications

Personal Attributes:

• Strong written and verbal communication skills

• Articulation skills

• Good team player

• Self-starter who requires minimal oversight

• Ability to prioritize and manage multiple tasks

• Process orientation and the ability to define and set up processes

Publicis Sapient Overview:

The Senior Associate People Senior Associate L1 in Data Engineering, you will translate client requirements into technical design, and implement components for data engineering solution. Utilize deep understanding of data integration and big data design principles in creating custom solutions or implementing package solutions. You will independently drive design discussions to insure the necessary health of the overall solution 

.

Job Summary:

As Senior Associate L1 in Data Engineering, you will do technical design, and implement components for data engineering solution. Utilize deep understanding of data integration and big data design principles in creating custom solutions or implementing package solutions. You will independently drive design discussions to insure the necessary health of the overall solution

The role requires a hands-on technologist who has strong programming background like Java / Scala / Python, should have experience in Data Ingestion, Integration and data Wrangling, Computation, Analytics pipelines and exposure to Hadoop ecosystem components. Having hands-on knowledge on at least one of AWS, GCP, Azure cloud platforms will be preferable.

Role & Responsibilities:

Job Title: Senior Associate L1 – Data Engineering

Your role is focused on Design, Development and delivery of solutions involving:

• Data Ingestion, Integration and Transformation

• Data Storage and Computation Frameworks, Performance Optimizations

• Analytics & Visualizations

• Infrastructure & Cloud Computing

• Data Management Platforms

• Build functionality for data ingestion from multiple heterogeneous sources in batch & real-time

• Build functionality for data analytics, search and aggregation

Experience Guidelines:

Mandatory Experience and Competencies:

# Competency

1.Overall 3.5+ years of IT experience with 1.5+ years in Data related technologies

2.Minimum 1.5 years of experience in Big Data technologies

3.Hands-on experience with the Hadoop stack – HDFS, sqoop, kafka, Pulsar, NiFi, Spark, Spark Streaming, Flink, Storm, hive, oozie, airflow and other components required in building end to end data pipeline. Working knowledge on real-time data pipelines is added advantage.

4.Strong experience in at least of the programming language Java, Scala, Python. Java preferable

5.Hands-on working knowledge of NoSQL and MPP data platforms like Hbase, MongoDb, Cassandra, AWS Redshift, Azure SQLDW, GCP BigQuery etc

Preferred Experience and Knowledge (Good to Have):

# Competency

1.Good knowledge of traditional ETL tools (Informatica, Talend, etc) and database technologies (Oracle, MySQL, SQL Server, Postgres) with hands on experience

2.Knowledge on data governance processes (security, lineage, catalog) and tools like Collibra, Alation etc

3.Knowledge on distributed messaging frameworks like ActiveMQ / RabbiMQ / Solace, search & indexing and Micro services architectures

4.Performance tuning and optimization of data pipelines

5.CI/CD – Infra provisioning on cloud, auto build & deployment pipelines, code quality

6.Working knowledge with data platform related services on at least 1 cloud platform, IAM and data security

7.Cloud data specialty and other related Big data technology certifications

Job Title: Senior Associate L1 – Data Engineering

Personal Attributes:

• Strong written and verbal communication skills

• Articulation skills

• Good team player

• Self-starter who requires minimal oversight

• Ability to prioritize and manage multiple tasks

• Process orientation and the ability to define and set up processes

Java/Scala + Data Engineer

Experience: 5-10 years

Location: Mumbai

Notice: Immediate to 30 days

Required Skills:

·       5+ years of software development experience.

·       Excellent skills in Java and/or Scala programming, with expertise in backend architectures, messaging technologies, and related frameworks.

·       Developing Data Pipelines (Batch/Streaming). Developing Complex data transformations, ETL Orchestration, Data Migration, Develop and Maintain Datawarehouse / Data Lakes.

·       Extensive experience in complex SQL queries, database development, and data engineering, including the development of procedures, packages, functions, and handling exceptions.

·       Knowledgeable in issue tracking tools (e.g., JIRA), code collaboration tools (e.g., Git/GitLab), and team collaboration tools (e.g., Confluence/Wiki).

·       Proficient in Linux/Unix, including shell scripting.

·       Ability to translate business and architectural features into quality, consistent software design.

·       Solid understanding of programming practices, emphasizing reusable, flexible, and reliable code.

Design a multi-tier data pipeline to feed data into applications for building a full-featured analytics environment. Develop high-quality code to support the platform's technical architecture and design. Participate and contribute to an effective software development lifecycle using Scrum and Agile. Collaborate with global teams and work as one team. what you get to do:

You'll work on the design, implementation, and maintenance of data pipelines. Design and build database schemas to handle large-scale data migration & transformation. Capable of designing a high-performance, scalable, distributed product in the cloudAWS, GCS. Review developmental frameworks, and coding standards, conducts code reviews and walkthroughs, and conduct in-depth design reviews. Identify gaps in the existing infrastructure and advocate for the necessary changes to close them. Who we are looking for:

4 to 7 years of industry experience working in Spark and Scala/Python. Working experience with big-data tech stacks like Spark, Kafka & Athena. Extensive experience in SQL query optimization/tuning and debugging SQL performance issues. Experience in ETL/ELT process to move data through the data processing pipeline. Be a fearless leader in championing smart design. Top 3 primary skills and expertise level requirements ( 1 to 5; 5 being expert)

Excellent programming experience in Scala or Python. Good experience in SQL queries and optimizations. 2 to 3 years of Spark experience. Nice to have experience in Airflow. Nice to have experience with AWS EMR, Lambda, and S3.

Employment Type - FULLTIME

Industry Type - Media / Entertainment / Internet

Seniority Level - Mid-Senior-Level

Work Experience(in years) - 4 - 7 Years

Education - B.Tech/B.E.

Skills - Python, Scala, Ms Sql Server, Aws

Lead Data Engineer

Data Engineers develop modern data architecture approaches to meet key business objectives and provide end-to-end data solutions. You might spend a few weeks with a new client on a deep technical review or a complete organizational review, helping them to understand the potential that data brings to solve their most pressing problems. On other projects, you might be acting as the architect, leading the design of technical solutions, or perhaps overseeing a program inception to build a new product. It could also be a software delivery project where you're equally happy coding and tech-leading the team to implement the solution.

Job responsibilities

·      You might spend a few weeks with a new client on a deep technical review or a complete organizational review, helping them to understand the potential that data brings to solve their most pressing problems

·      You will partner with teammates to create complex data processing pipelines in order to solve our clients' most ambitious challenges

·      You will collaborate with Data Scientists in order to design scalable implementations of their models

·      You will pair to write clean and iterative code based on TDD

·      Leverage various continuous delivery practices to deploy, support and operate data pipelines

·      Advise and educate clients on how to use different distributed storage and computing technologies from the plethora of options available

·      Develop and operate modern data architecture approaches to meet key business objectives and provide end-to-end data solutions

·      Create data models and speak to the tradeoffs of different modeling approaches

·      On other projects, you might be acting as the architect, leading the design of technical solutions, or perhaps overseeing a program inception to build a new product

·      Seamlessly incorporate data quality into your day-to-day work as well as into the delivery process

·      Assure effective collaboration between Thoughtworks' and the client's teams, encouraging open communication and advocating for shared outcomes

Job qualifications Technical skills

·      You are equally happy coding and leading a team to implement a solution

·      You have a track record of innovation and expertise in Data Engineering

·      You're passionate about craftsmanship and have applied your expertise across a range of industries and organizations

·      You have a deep understanding of data modelling and experience with data engineering tools and platforms such as Kafka, Spark, and Hadoop

·      You have built large-scale data pipelines and data-centric applications using any of the distributed storage platforms such as HDFS, S3, NoSQL databases (Hbase, Cassandra, etc.) and any of the distributed processing platforms like Hadoop, Spark, Hive, Oozie, and Airflow in a production setting

·      Hands on experience in MapR, Cloudera, Hortonworks and/or cloud (AWS EMR, Azure HDInsights, Qubole etc.) based Hadoop distributions

·      You are comfortable taking data-driven approaches and applying data security strategy to solve business problems

·      You're genuinely excited about data infrastructure and operations with a familiarity working in cloud environments

·      Working with data excites you: you have created Big data architecture, you can build and operate data pipelines, and maintain data storage, all within distributed systems

Professional skills

·      Advocate your data engineering expertise to the broader tech community outside of Thoughtworks, speaking at conferences and acting as a mentor for more junior-level data engineers

·      You're resilient and flexible in ambiguous situations and enjoy solving problems from technical and business perspectives

·      An interest in coaching others, sharing your experience and knowledge with teammates

·      You enjoy influencing others and always advocate for technical excellence while being open to change when needed

Greetings!!!!

We are looking for a data engineer for one of our premium clients for their Chennai and Tirunelveli location

Required Education/Experience

● Bachelor’s degree in computer Science or related field

● 5-7 years’ experience in the following:

● Snowflake, Databricks management,

● Python and AWS Lambda

● Scala and/or Java

● Data integration service, SQL and Extract Transform Load (ELT)

● Azure or AWS for development and deployment

● Jira or similar tool during SDLC

● Experience managing codebase using Code repository in Git/GitHub or Bitbucket

● Experience working with a data warehouse.

● Familiarity with structured and semi-structured data formats including JSON, Avro, ORC, Parquet, or XML

● Exposure to working in an agile work environment

DATA ENGINEERING CONSULTANT

About NutaNXT: NutaNXT is a next-gen Software Product Engineering services provider building ground-breaking products using AI/ML, Data Analytics, IOT, Cloud & new emerging technologies disrupting the global markets. Our mission is to help clients leverage our specialized Digital Product Engineering capabilities on Data Engineering, AI Automations, Software Full stack solutions and services to build best-in-class products and stay ahead of the curve. You will get a chance to work on multiple projects critical to NutaNXT needs with opportunities to learn, develop new skills,switch teams and projects as you and our fast-paced business grow and evolve. Location: Pune Experience: 6 to 8 years

Job Description: NutaNXT is looking for supporting the planning and implementation of data design services, providing sizing and configuration assistance and performing needs assessments. Delivery of architectures for transformations and modernizations of enterprise data solutions using Azure cloud data technologies. As a Data Engineering Consultant, you will collect, aggregate, store, and reconcile data in support of Customer's business decisions. You will design and build data pipelines, data streams, data service APIs, data generators and other end-user information portals and insight tools.

Mandatory Skills: -

1. Demonstrable experience in enterprise level data platforms involving implementation of end-to-end data pipelines with Python or Scala - Hands-on experience with at least one of the leading public cloud data platforms (Ideally Azure)
2. - Experience with different Databases (like column-oriented database, NoSQL database, RDBMS)
3. - Experience in architecting data pipelines and solutions for both streaming and batch integrations using tools/frameworks like Azure Databricks, Azure Data Factory, Spark, Spark Streaming, etc
4. . - Understanding of data modeling, warehouse design and fact/dimension concepts - Good Communication

Good To Have:

Certifications for any of the cloud services (Ideally Azure)

• Experience working with code repositories and continuous integration • Understanding of development and project methodologies

Why Join Us?

We offer Innovative work in AI & Data Engineering Space, with a unique, diverse workplace environment having a Continuous learning and development opportunities. These are just some of the reasons we're consistently being recognized as one of the best companies to work for, and why our people choose to grow careers at NutaNXT. We also offer a highly flexible, self-driven, remote work culture which fosters the best of innovation, creativity and work-life balance, market industry-leading compensation which we believe help us consistently deliver to our clients and grow in the highly competitive, fast evolving Digital Engineering space with a strong focus on building advanced software products for clients in the US, Europe and APAC regions.

1. Big data developer with 8+ years of professional IT experience with expertise in Hadoop ecosystem components in ingestion, Data modeling, querying, processing, storage, analysis, Data Integration and Implementing enterprise level systems spanning Big Data.
2. A skilled developer with strong problem solving, debugging and analytical capabilities, who actively engages in understanding customer requirements.
3. Expertise in Apache Hadoop ecosystem components like Spark, Hadoop Distributed File Systems(HDFS), HiveMapReduce, Hive, Sqoop, HBase, Zookeeper, YARN, Flume, Pig, Nifi, Scala and Oozie.
4. Hands on experience in creating real - time data streaming solutions using Apache Spark core, Spark SQL & DataFrames, Kafka, Spark streaming and Apache Storm.
5. Excellent knowledge of Hadoop architecture and daemons of Hadoop clusters, which include Name node,Data node, Resource manager, Node Manager and Job history server.
6. Worked on both Cloudera and Horton works in Hadoop Distributions. Experience in managing Hadoop clustersusing Cloudera Manager tool.
7. Well versed in installation, Configuration, Managing of Big Data and underlying infrastructure of Hadoop Cluster.
8. Hands on experience in coding MapReduce/Yarn Programs using Java, Scala and Python for analyzing Big Data.
9. Exposure to Cloudera development environment and management using Cloudera Manager.
10. Extensively worked on Spark using Scala on cluster for computational (analytics), installed it on top of Hadoop performed advanced analytical application by making use of Spark with Hive and SQL/Oracle .
11. Implemented Spark using PYTHON and utilizing Data frames and Spark SQL API for faster processing of data and handled importing data from different data sources into HDFS using Sqoop and performing transformations using Hive, MapReduce and then loading data into HDFS.
12. Used Spark Data Frames API over Cloudera platform to perform analytics on Hive data.
13. Hands on experience in MLlib from Spark which are used for predictive intelligence, customer segmentation and for smooth maintenance in Spark streaming.
14. Experience in using Flume to load log files into HDFS and Oozie for workflow design and scheduling.
15. Experience in optimizing MapReduce jobs to use HDFS efficiently by using various compression mechanisms.
16. Working on creating data pipeline for different events of ingestion, aggregation, and load consumer response data into Hive external tables in HDFS location to serve as feed for tableau dashboards.
17. Hands on experience in using Sqoop to import data into HDFS from RDBMS and vice-versa.
18. In-depth Understanding of Oozie to schedule all Hive/Sqoop/HBase jobs.
19. Hands on expertise in real time analytics with Apache Spark.
20. Experience in converting Hive/SQL queries into RDD transformations using Apache Spark, Scala and Python.
21. Extensive experience in working with different ETL tool environments like SSIS, Informatica and reporting tool environments like SQL Server Reporting Services (SSRS).
22. Experience in Microsoft cloud and setting cluster in Amazon EC2 & S3 including the automation of setting & extending the clusters in AWS Amazon cloud.
23. Extensively worked on Spark using Python on cluster for computational (analytics), installed it on top of Hadoop performed advanced analytical application by making use of Spark with Hive and SQL.
24. Strong experience and knowledge of real time data analytics using Spark Streaming, Kafka and Flume.
25. Knowledge in installation, configuration, supporting and managing Hadoop Clusters using Apache, Cloudera (CDH3, CDH4) distributions and on Amazon web services (AWS).
26. Experienced in writing Ad Hoc queries using Cloudera Impala, also used Impala analytical functions.
27. Experience in creating Data frames using PySpark and performing operation on the Data frames using Python.
28. In depth understanding/knowledge of Hadoop Architecture and various components such as HDFS and MapReduce Programming Paradigm, High Availability and YARN architecture.
29. Establishing multiple connections to different Redshift clusters (Bank Prod, Card Prod, SBBDA Cluster) and provide the access for pulling the information we need for analysis. 
30. Generated various kinds of knowledge reports using Power BI based on Business specification. 
31. Developed interactive Tableau dashboards to provide a clear understanding of industry specific KPIs using quick filters and parameters to handle them more efficiently.
32. Well Experience in projects using JIRA, Testing, Maven and Jenkins build tools.
33. Experienced in designing, built, and deploying and utilizing almost all the AWS stack (Including EC2, S3,), focusing on high-availability, fault tolerance, and auto-scaling.
34. Good experience with use-case development, with Software methodologies like Agile and Waterfall.
35. Working knowledge of Amazon's Elastic Cloud Compute( EC2 ) infrastructure for computational tasks and Simple Storage Service ( S3 ) as Storage mechanism.
36. Good working experience in importing data using Sqoop, SFTP from various sources like RDMS, Teradata, Mainframes, Oracle, Netezza to HDFS and performed transformations on it using Hive, Pig and Spark .
37. Extensive experience in Text Analytics, developing different Statistical Machine Learning solutions to various business problems and generating data visualizations using Python and R.
38. Proficient in NoSQL databases including HBase, Cassandra, MongoDB and its integration with Hadoop cluster.
39. Hands on experience in Hadoop Big data technology working on MapReduce, Pig, Hive as Analysis tool, Sqoop and Flume data import/export tools.

Big Data Engineer- SCALA

Required Skills:

1. Experience in building modern and scalable REST – based microservices using Scala, preferably with Play as MVC framework.

2. Expertise with functional programming using SCALA

3. Experience in implementing RESTful web services in Scala, Java or similar languages.

4. Experience with No SQL and SQL databases.

5. Experience in information retrieval and machine learning

6. Experience/ knowledge in big data using Scala spark, ML, Kafka, and Elastic search will be plus.

Job Description:

As an Azure Data Engineer, your role will involve designing, developing, and maintaining data solutions on the Azure platform. You will be responsible for building and optimizing data pipelines, ensuring data quality and reliability, and implementing data processing and transformation logic. Your expertise in Azure Databricks, Python, SQL, Azure Data Factory (ADF), PySpark, and Scala will be essential for performing the following key responsibilities:

Designing and developing data pipelines: You will design and implement scalable and efficient data pipelines using Azure Databricks, PySpark, and Scala. This includes data ingestion, data transformation, and data loading processes.

Data modeling and database design: You will design and implement data models to support efficient data storage, retrieval, and analysis. This may involve working with relational databases, data lakes, or other storage solutions on the Azure platform.

Data integration and orchestration: You will leverage Azure Data Factory (ADF) to orchestrate data integration workflows and manage data movement across various data sources and targets. This includes scheduling and monitoring data pipelines.

Data quality and governance: You will implement data quality checks, validation rules, and data governance processes to ensure data accuracy, consistency, and compliance with relevant regulations and standards.

Performance optimization: You will optimize data pipelines and queries to improve overall system performance and reduce processing time. This may involve tuning SQL queries, optimizing data transformation logic, and leveraging caching techniques.

Monitoring and troubleshooting: You will monitor data pipelines, identify performance bottlenecks, and troubleshoot issues related to data ingestion, processing, and transformation. You will work closely with cross-functional teams to resolve data-related problems.

Documentation and collaboration: You will document data pipelines, data flows, and data transformation processes. You will collaborate with data scientists, analysts, and other stakeholders to understand their data requirements and provide data engineering support.

Skills and Qualifications:

Strong experience with Azure Databricks, Python, SQL, ADF, PySpark, and Scala.

Proficiency in designing and developing data pipelines and ETL processes.

Solid understanding of data modeling concepts and database design principles.

Familiarity with data integration and orchestration using Azure Data Factory.

Knowledge of data quality management and data governance practices.

Experience with performance tuning and optimization of data pipelines.

Strong problem-solving and troubleshooting skills related to data engineering.

Excellent collaboration and communication skills to work effectively in cross-functional teams.

Understanding of cloud computing principles and experience with Azure services.

As Conviva is expanding, we are building products providing deep insights into end-user experience for our customers.

Platform and TLB Team

The vision for the TLB team is to build data processing software that works on terabytes of streaming data in real-time. Engineer the next-gen Spark-like system for in-memory computation of large time-series datasets – both Spark-like backend infra and library-based programming model. Build a horizontally and vertically scalable system that analyses trillions of events per day within sub-second latencies. Utilize the latest and greatest big data technologies to build solutions for use cases across multiple verticals. Lead technology innovation and advancement that will have a big business impact for years to come. Be part of a worldwide team building software using the latest technologies and the best of software development tools and processes.

What You’ll Do

This is an individual contributor position. Expectations will be on the below lines:

• Design, build and maintain the stream processing, and time-series analysis system which is at the heart of Conviva’s products
• Responsible for the architecture of the Conviva platform
• Build features, enhancements, new services, and bug fixing in Scala and Java on a Jenkins-based pipeline to be deployed as Docker containers on Kubernetes
• Own the entire lifecycle of your microservice including early specs, design, technology choice, development, unit-testing, integration-testing, documentation, deployment, troubleshooting, enhancements, etc.
• Lead a team to develop a feature or parts of a product
• Adhere to the Agile model of software development to plan, estimate, and ship per business priority

What you need to succeed

• 5+ years of work experience in software development of data processing products.
• Engineering degree in software or equivalent from a premier institute.
• Excellent knowledge of fundamentals of Computer Science like algorithms and data structures. Hands-on with functional programming and know-how of its concepts
• Excellent programming and debugging skills on the JVM. Proficient in writing code in Scala/Java/Rust/Haskell/Erlang that is reliable, maintainable, secure, and performant
• Experience with big data technologies like Spark, Flink, Kafka, Druid, HDFS, etc.
• Deep understanding of distributed systems concepts and scalability challenges including multi-threading, concurrency, sharding, partitioning, etc.
• Experience/knowledge of Akka/Lagom framework and/or stream processing technologies like RxJava or Project Reactor will be a big plus. Knowledge of design patterns like event-streaming, CQRS and DDD to build large microservice architectures will be a big plus
• Excellent communication skills. Willingness to work under pressure. Hunger to learn and succeed. Comfortable with ambiguity. Comfortable with complexity

Underpinning the Conviva platform is a rich history of innovation. More than 60 patents represent award-winning technologies and standards, including first-of-its kind-innovations like time-state analytics and AI-automated data modeling, that surfaces actionable insights. By understanding real-world human experiences and having the ability to act within seconds of observation, our customers can solve business-critical issues and focus on growing their business ahead of the competition. Examples of the brands Conviva has helped fuel streaming growth for include: DAZN, Disney+, HBO, Hulu, NBCUniversal, Paramount+, Peacock, Sky, Sling TV, Univision and Warner Bros Discovery.  

Privately held, Conviva is headquartered in Silicon Valley, California with offices and people around the globe. For more information, visit us at www.conviva.com. Join us to help extend our leadership position in big data streaming analytics to new audiences and markets! 

About Kloud9:

Kloud9 exists with the sole purpose of providing cloud expertise to the retail industry. Our team of cloud architects, engineers and developers help retailers launch a successful cloud initiative so you can quickly realise the benefits of cloud technology. Our standardised, proven cloud adoption methodologies reduce the cloud adoption time and effort so you can directly benefit from lower migration costs.

Kloud9 was founded with the vision of bridging the gap between E-commerce and cloud. The E-commerce of any industry is limiting and poses a huge challenge in terms of the finances spent on physical data structures.

At Kloud9, we know migrating to the cloud is the single most significant technology shift your company faces today. We are your trusted advisors in transformation and are determined to build a deep partnership along the way. Our cloud and retail experts will ease your transition to the cloud.

Our sole focus is to provide cloud expertise to retail industry giving our clients the empowerment that will take their business to the next level. Our team of proficient architects, engineers and developers have been designing, building and implementing solutions for retailers for an average of more than 20 years.

We are a cloud vendor that is both platform and technology independent. Our vendor independence not just provides us with a unique perspective into the cloud market but also ensures that we deliver the cloud solutions available that best meet our clients' requirements.

●    Overall 8+ Years of Experience in Web Application development.

●    5+ Years of development experience with JAVA8 , Springboot, Microservices and middleware

●    3+ Years of Designing Middleware using Node JS platform.

●    good to have 2+ Years of Experience in using NodeJS along with AWS Serverless platform.

●    Good Experience with Javascript / TypeScript, Event Loops, ExpressJS, GraphQL, SQL DB (MySQLDB), NoSQL DB(MongoDB) and YAML templates.

●    Good Experience with TDD Driven Development and Automated Unit Testing.

●    Good Experience with exposing and consuming Rest APIs in Java 8, Springboot platform and Swagger API contracts.

●    Good Experience in building NodeJS middleware performing Transformations, Routing, Aggregation, Orchestration and Authentication(JWT/OAUTH).

●    Experience supporting and working with cross-functional teams in a dynamic environment.

●    Experience working in Agile Scrum Methodology.

●    Very good Problem-Solving Skills.

●    Very good learner and passion for technology.

●     Excellent verbal and written communication skills in English

●     Ability to communicate effectively with team members and business stakeholders

Secondary Skill Requirements:

● Experience working with any of Loopback, NestJS, Hapi.JS, Sails.JS, Passport.JS

Why Explore a Career at Kloud9:

With job opportunities in prime locations of US, London, Poland and Bengaluru, we help build your career paths in cutting edge technologies of AI, Machine Learning and Data Science. Be part of an inclusive and diverse workforce that's changing the face of retail technology with their creativity and innovative solutions. Our vested interest in our employees translates to deliver the best products and solutions to our customers.

InViz is Bangalore Based Startup helping Enterprises simplifying the Search and Discovery experiences for both their end customers as well as their internal users. We use state-of-the-art technologies in Computer Vision, Natural Language Processing, Text Mining, and other ML techniques to extract information/concepts from data of different formats- text, images, videos and make them easily discoverable through simple human-friendly touchpoints. 

TSDE - Data 

Data Engineer:

• Should have total 3-6 Yrs of experience in Data Engineering.
• Person should have experience in coding data pipeline on GCP. 
• Prior experience on Hadoop systems is ideal as candidate may not have total GCP experience. 
• Strong on programming languages like Scala, Python, Java. 
• Good understanding of various data storage formats and it’s advantages. 
• Should have exposure on GCP tools to develop end to end data pipeline for various scenarios (including ingesting data from traditional data bases as well as integration of API based data sources). 
• Should have Business mindset to understand data and how it will be used for BI and Analytics purposes. 
• Data Engineer Certification preferred 

Roles and Responsibilities

Roles and Responsibilities

Big Data Engineer: 5+ yrs.
Immediate Joiner

• Expertise in building AWS Data Engineering pipelines with AWS Glue -> Athena -> Quick sight
• Experience in developing lambda functions with AWS Lambda
• Expertise with Spark/PySpark – Candidate should be hands on with PySpark code and should be able to do transformations with Spark
• Should be able to code in Python and Scala.
• Snowflake experience will be a plus
• We can start keeping Hadoop and Hive requirements as good to have or understanding of is enough rather than keeping it as a desirable requirement.

Bigdata with cloud:

Experience : 5-10 years

Location : Hyderabad/Chennai

Notice period : 15-20 days Max

1.  Expertise in building AWS Data Engineering pipelines with AWS Glue -> Athena -> Quick sight

2.  Experience in developing lambda functions with AWS Lambda

3.  Expertise with Spark/PySpark – Candidate should be hands on with PySpark code and should be able to do transformations with Spark

4.  Should be able to code in Python and Scala.

5.  Snowflake experience will be a plus

1. Expertise in building AWS Data Engineering pipelines with AWS Glue -> Athena -> Quick sight
2. Experience in developing lambda functions with AWS Lambda
3. Expertise with Spark/PySpark – Candidate should be hands on with PySpark code and should be able to do transformations with Spark
4. Should be able to code in Python and Scala.
5. Snowflake experience will be a plus

• Manages the delivery of large, complex Data Science projects using appropriate frameworks and collaborating with stake holders to manage scope and risk. Help the AI/ML Solution
• Analyst to build solution as per customer need on our platform Newgen AI Cloud. Drives profitability and continued success by managing service quality and cost and leading delivery. Proactively support sales through innovative solutions and delivery excellence.
•  

Hiring - Python Developer Freelance Consultant (WFH-Remote)

Greetings from Deltacubes Technology!!

Skillset Required:

Python

Pyspark

AWS

Scala

Experience:

5+ years

Thanks

Bavithra

1. Data Engineer

 Required skill set: AWS GLUE, AWS LAMBDA, AWS SNS/SQS, AWS ATHENA, SPARK, SNOWFLAKE, PYTHON

Mandatory Requirements  

• Experience in AWS Glue
• Experience in Apache Parquet 
• Proficient in AWS S3 and data lake 
• Knowledge of Snowflake
• Understanding of file-based ingestion best practices.
• Scripting language - Python & pyspark 

CORE RESPONSIBILITIES 

• Create and manage cloud resources in AWS 
• Data ingestion from different data sources which exposes data using different technologies, such as: RDBMS, REST HTTP API, flat files, Streams, and Time series data based on various proprietary systems. Implement data ingestion and processing with the help of Big Data technologies 
• Data processing/transformation using various technologies such as Spark and Cloud Services. You will need to understand your part of business logic and implement it using the language supported by the base data platform 
• Develop automated data quality check to make sure right data enters the platform and verifying the results of the calculations 
• Develop an infrastructure to collect, transform, combine and publish/distribute customer data.
• Define process improvement opportunities to optimize data collection, insights and displays.
• Ensure data and results are accessible, scalable, efficient, accurate, complete and flexible 
• Identify and interpret trends and patterns from complex data sets 
• Construct a framework utilizing data visualization tools and techniques to present consolidated analytical and actionable results to relevant stakeholders. 
• Key participant in regular Scrum ceremonies with the agile teams  
• Proficient at developing queries, writing reports and presenting findings 
• Mentor junior members and bring best industry practices 

 QUALIFICATIONS 

• 5-7+ years’ experience as data engineer in consumer finance or equivalent industry (consumer loans, collections, servicing, optional product, and insurance sales) 
• Strong background in math, statistics, computer science, data science or related discipline
• Advanced knowledge one of language: Java, Scala, Python, C# 
• Production experience with: HDFS, YARN, Hive, Spark, Kafka, Oozie / Airflow, Amazon Web Services (AWS), Docker / Kubernetes, Snowflake  
• Proficient with
• Data mining/programming tools (e.g. SAS, SQL, R, Python)
• Database technologies (e.g. PostgreSQL, Redshift, Snowflake. and Greenplum)
• Data visualization (e.g. Tableau, Looker, MicroStrategy)
• Comfortable learning about and deploying new technologies and tools. 
• Organizational skills and the ability to handle multiple projects and priorities simultaneously and meet established deadlines. 
• Good written and oral communication skills and ability to present results to non-technical audiences 
• Knowledge of business intelligence and analytical tools, technologies and techniques.

Familiarity and experience in the following is a plus:  

• AWS certification
• Spark Streaming 
• Kafka Streaming / Kafka Connect 
• ELK Stack 
• Cassandra / MongoDB 
• CI/CD: Jenkins, GitLab, Jira, Confluence other related tools

Job Description

1. Solid technical skills with a proven and successful history working with data at scale and empowering organizations through data
2. Big data processing frameworks: Spark, Scala, Hadoop, Hive, Kafka, EMR with Python
3. Advanced experience and hands-on architecture and administration experience on big data platforms

LogiNext is looking for a technically savvy and passionate Software Engineer - Data Science to analyze large amounts of raw information to find patterns that will help improve our company. We will rely on you to build data products to extract valuable business insights.

In this role, you should be highly analytical with a knack for analysis, math and statistics. Critical thinking and problem-solving skills are essential for interpreting data. We also want to see a passion for machine-learning and research.

Your goal will be to help our company analyze trends to make better decisions. Without knowledge of how the software works, data scientists might have difficulty in work. Apart from experience in developing R and Python, they must know modern approaches to software development and their impact. DevOps continuous integration and deployment, experience in cloud computing are everyday skills to manage and process data.

Responsibilities:

Identify valuable data sources and automate collection processes Undertake preprocessing of structured and unstructured data Analyze large amounts of information to discover trends and patterns Build predictive models and machine-learning algorithms Combine models through ensemble modeling Present information using data visualization techniques Propose solutions and strategies to business challenges Collaborate with engineering and product development teams

Requirements:

Bachelors degree or higher in Computer Science, Information Technology, Information Systems, Statistics, Mathematics, Commerce, Engineering, Business Management, Marketing or related field from top-tier school 2 to 3 year experince in in data mining, data modeling, and reporting. Understading of SaaS based products and services. Understanding of machine-learning and operations research Experience of R, SQL and Python; familiarity with Scala, Java or C++ is an asset Experience using business intelligence tools (e.g. Tableau) and data frameworks (e.g. Hadoop) Analytical mind and business acumen and problem-solving aptitude Excellent communication and presentation skills Proficiency in Excel for data management and manipulation Experience in statistical modeling techniques and data wrangling Able to work independently and set goals keeping business objectives in mind

LogiNext is looking for a technically savvy and passionate Senior Software Engineer - Data Science to analyze large amounts of raw information to find patterns that will help improve our company. We will rely on you to build data products to extract valuable business insights.

In this role, you should be highly analytical with a knack for analysis, math and statistics. Critical thinking and problem-solving skills are essential for interpreting data. We also want to see a passion for machine-learning and research.

Your goal will be to help our company analyze trends to make better decisions. Without knowledge of how the software works, data scientists might have difficulty in work. Apart from experience in developing R and Python, they must know modern approaches to software development and their impact. DevOps continuous integration and deployment, experience in cloud computing are everyday skills to manage and process data.

Responsibilities :

Adapting and enhancing machine learning techniques based on physical intuition about the domain Design sampling methodology, prepare data, including data cleaning, univariate analysis, missing value imputation, , identify appropriate analytic and statistical methodology, develop predictive models and document process and results Lead projects both as a principal investigator and project manager, responsible for meeting project requirements on schedule and on budget Coordinate and lead efforts to innovate by deriving insights from heterogeneous sets of data generated by our suite of Aerospace products Support and mentor data scientists Maintain and work with our data pipeline that transfers and processes several terabytes of data using Spark, Scala, Python, Apache Kafka, Pig/Hive & Impala Work directly with application teams/partners (internal clients such as Xbox, Skype, Office) to understand their offerings/domain and help them become successful with data so they can run controlled experiments (a/b testing) Understand the data generated by experiments, and producing actionable, trustworthy conclusions from them Apply data analysis, data mining and data processing to present data clearly and develop experiments (ab testing) Work with development team to build tools for data logging and repeatable data tasks tol accelerate and automate data scientist duties

Requirements:

Bachelor’s or Master’s degree in Computer Science, Math, Physics, Engineering, Statistics or other technical field. PhD preferred 4 to 7 years of experience in data mining, data modeling, and reporting 3+ years of experience working with large data sets or do large scale quantitative analysis Expert SQL scripting required Development experience in one of the following: Scala, Java, Python, Perl, PHP, C++ or C# Experience working with Hadoop, Pig/Hive, Spark, MapReduce Ability to drive projects Basic understanding of statistics – hypothesis testing, p-values, confidence intervals, regression, classification, and optimization are core lingo Analysis - Should be able to perform Exploratory Data Analysis and get actionable insights from the data, with impressive visualization. Modeling - Should be familiar with ML concepts and algorithms; understanding of the internals and pros/cons of models is required. Strong algorithmic problem-solving skills Experience manipulating large data sets through statistical software (ex. R, SAS) or other methods Superior verbal, visual and written communication skills to educate and work with cross functional teams on controlled experiments Experimentation design or A/B testing experience is preferred. Experince in team management.

• 5+ years of experience in a Data Engineering role on cloud environment

• Must have good experience in Scala/PySpark (preferably on data-bricks environment)

• Extensive experience with Transact-SQL.
• Experience in Data-bricks/Spark.

• Strong experience in Dataware house projects
• Expertise in database development projects with ETL processes.
• Manage and maintain data engineering pipelines

• Develop batch processing, streaming and integration solutions
• Experienced in building and operationalizing large-scale enterprise data solutions and applications

• Using one or more of Azure data and analytics services in combination with custom solutions
• Azure Data Lake, Azure SQL DW (Synapse), and SQL Database products or equivalent products from other cloud services providers

• In-depth understanding of data management (e. g. permissions, security, and monitoring).
• Cloud repositories for e.g. Azure GitHub, Git
• Experience in an agile environment (Prefer Azure DevOps).

Good to have

• Manage source data access security
• Automate Azure Data Factory pipelines
• Continuous Integration/Continuous deployment (CICD) pipelines, Source Repositories
• Experience in implementing and maintaining CICD pipelines
• Power BI understanding, Delta Lake house architecture
• Knowledge of software development best practices.
• Excellent analytical and organization skills.
• Effective working in a team as well as working independently.
• Strong written and verbal communication skills.
• Expertise in database development projects and ETL processes.

• 15+ years of Hands-on technical application architecture experience and Application build/ modernization experience

• 15+ years of experience as a technical specialist in Customer-facing roles.

• Ability to travel to client locations as needed (25-50%)

• Extensive experience architecting, designing and programming applications in an AWS Cloud environment

• Experience with designing and building applications using AWS services such as EC2, AWS Elastic Beanstalk, AWS OpsWorks

• Experience architecting highly available systems that utilize load balancing, horizontal scalability and high availability

• Hands-on programming skills in any of the following: Python, Java, Node.js, Ruby, .NET or Scala

• Agile software development expert
• Experience with continuous integration tools (e.g. Jenkins)

• Hands-on familiarity with CloudFormation

• Experience with configuration management platforms (e.g. Chef, Puppet, Salt, or Ansible)

• Strong scripting skills (e.g. Powershell, Python, Bash, Ruby, Perl, etc.)

• Strong practical application development experience on Linux and Windows-based systems

• Extra curricula software development passion (e.g. active open source contributor)