Enthusiastic Cloud-ML Engineers with a keen sense of curiosity

LogiNext is looking for a technically savvy and passionate Junior 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 0 to 1 year experince in in data mining, data modeling, and reporting. Understading of SaaS based products and services. Understanding of machine-learning and operations research Knowledge of R, SQL and Python; familiarity with Scala, Java or C++ is an asset Knowledge 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

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 

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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

Sizzle is an exciting new startup that’s changing the world of gaming.  At Sizzle, we’re building AI to automate gaming highlights, directly from Twitch and YouTube streams. 

For this role, we're looking for someone that ideally loves to watch video gaming content on Twitch and YouTube. Specifically, you will help generate training data for all the AI we are building. This will include gathering screenshots, clips and other data from gaming videos on Twitch and YouTube.  You will then be responsible for labeling and annotating them. You will work very closely with our AI engineers.

You will:

• Gather training data as specified by the management and engineering team
• Label and annotate all the training data
• Ensure all data is prepped and ready to feed into the AI models
• Revise the training data as specified by the engineering team
• Test the output of the AI models and update training data needs

You should have the following qualities:

• Willingness to work hard and hit deadlines
• Work well with people
• Be able to work remotely (if not in Bangalore)
• Interested in learning about AI and computer vision
• Willingness to learn rapidly on the job
• Ideally a gamer or someone interested in watching gaming content online

Skills:

Data labeling, annotation, AI, computer vision, gaming

Work Experience:  0 years to 3 years

About Sizzle

You will be responsible for designing, building, and maintaining data pipelines that handle Real-world data at Compile. You will be handling both inbound and outbound data deliveries at Compile for datasets including Claims, Remittances, EHR, SDOH, etc.

You will

• Work on building and maintaining data pipelines (specifically RWD).
• Build, enhance and maintain existing pipelines in pyspark, python and help build analytical insights and datasets.
• Scheduling and maintaining pipeline jobs for RWD.
• Develop, test, and implement data solutions based on the design.
• Design and implement quality checks on existing and new data pipelines.
• Ensure adherence to security and compliance that is required for the products.
• Maintain relationships with various data vendors and track changes and issues across vendors and deliveries.

You have

• Hands-on experience with ETL process (min of 5 years).
• Excellent communication skills and ability to work with multiple vendors.
• High proficiency with Spark, SQL.
• Proficiency in Data modeling, validation, quality check, and data engineering concepts.
• Experience in working with big-data processing technologies using - databricks, dbt, S3, Delta lake, Deequ, Griffin, Snowflake, BigQuery.
• Familiarity with version control technologies, and CI/CD systems.
• Understanding of scheduling tools like Airflow/Prefect.
• Min of 3 years of experience managing data warehouses.
• Familiarity with healthcare datasets is a plus.

Compile embraces diversity and equal opportunity in a serious way. We are committed to building a team of people from many backgrounds, perspectives, and skills. We know the more inclusive we are, the better our work will be.         

Hi All,

We are hiring Data Engineer for one of our client for Bangalore & Chennai Location.


Strong Knowledge of SCCM, App V, and Intune infrastructure.

Powershell/VBScript/Python,

Windows Installer

Knowledge of Windows 10 registry

Application Repackaging

Application Sequencing with App-v

Deploying and troubleshooting applications, packages, and Task Sequences.

Security patch deployment and remediation

Windows operating system patching and defender updates

Thanks,
Mohan.G

Intro

Our data and risk team is the core pillar of our business that harnesses alternative data sources to guide the decisions we make at Rely. The team designs, architects, as well as develop and maintain a scalable data platform the powers our machine learning models. Be part of a team that will help millions of consumers across Asia, to be effortlessly in control of their spending and make better decisions.

What will you do
The data engineer is focused on making data correct and accessible, and building scalable systems to access/process it. Another major responsibility is helping AI/ML Engineers write better code.

• Optimize and automate ingestion processes for a variety of data sources such as: click stream, transactional and many other sources.

• Create and maintain optimal data pipeline architecture and ETL processes
• Assemble large, complex data sets that meet functional / non-functional business requirements.
• Develop data pipeline and infrastructure to support real-time decisions
• Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS big data' technologies.
• Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.
• Work with stakeholders to assist with data-related technical issues and support their data infrastructure needs.
  
  

What will you need
• 2+ hands-on experience building and implementation of large scale production pipeline and Data Warehouse
• Experience dealing with large scale

• Proficiency in writing and debugging complex SQLs
• Experience working with AWS big data tools
  • Ability to lead the project and implement best data practises and technology

Data Pipelining

• Strong command in building & optimizing data pipelines, architectures and data sets
• Strong command on relational SQL & noSQL databases including Postgres
• Data pipeline and workflow management tools: Azkaban, Luigi, Airflow, etc.

Big Data: Strong experience in big data tools & applications

• Tools: Hadoop, Spark, HDFS etc
• AWS cloud services: EC2, EMR, RDS, Redshift
• Stream-processing systems: Storm, Spark-Streaming, Flink etc.
• Message queuing: RabbitMQ, Spark etc
  
  

Software Development & Debugging

• Strong experience in object-oriented programming/object function scripting languages: Python, Java, C++, Scala, etc
• Strong hold on data structures & algorithms

What would be a bonus

• Prior experience working in a fast-growth Startup
• Prior experience in the payments, fraud, lending, advertising companies dealing with large scale data