Software developer

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

Position Overview: We are seeking a talented Data Engineer with expertise in Power BI to join our team. The ideal candidate will be responsible for designing and implementing data pipelines, as well as developing insightful visualizations and reports using Power BI. Additionally, the candidate should have strong skills in Python, data analytics, PySpark, and Databricks. This role requires a blend of technical expertise, analytical thinking, and effective communication skills.

Key Responsibilities:

1. Design, develop, and maintain data pipelines and architectures using PySpark and Databricks.
2. Implement ETL processes to extract, transform, and load data from various sources into data warehouses or data lakes.
3. Collaborate with data analysts and business stakeholders to understand data requirements and translate them into actionable insights.
4. Develop interactive dashboards, reports, and visualizations using Power BI to communicate key metrics and trends.
5. Optimize and tune data pipelines for performance, scalability, and reliability.
6. Monitor and troubleshoot data infrastructure to ensure data quality, integrity, and availability.
7. Implement security measures and best practices to protect sensitive data.
8. Stay updated with emerging technologies and best practices in data engineering and data visualization.
9. Document processes, workflows, and configurations to maintain a comprehensive knowledge base.

Requirements:

1. Bachelor’s degree in Computer Science, Engineering, or related field. (Master’s degree preferred)
2. Proven experience as a Data Engineer with expertise in Power BI, Python, PySpark, and Databricks.
3. Strong proficiency in Power BI, including data modeling, DAX calculations, and creating interactive reports and dashboards.
4. Solid understanding of data analytics concepts and techniques.
5. Experience working with Big Data technologies such as Hadoop, Spark, or Kafka.
6. Proficiency in programming languages such as Python and SQL.
7. Hands-on experience with cloud platforms like AWS, Azure, or Google Cloud.
8. Excellent analytical and problem-solving skills with attention to detail.
9. Strong communication and collaboration skills to work effectively with cross-functional teams.
10. Ability to work independently and manage multiple tasks simultaneously in a fast-paced environment.

Preferred Qualifications:

• Advanced degree in Computer Science, Engineering, or related field.
• Certifications in Power BI or related technologies.
• Experience with data visualization tools other than Power BI (e.g., Tableau, QlikView).
• Knowledge of machine learning concepts and frameworks.

Role: Principal Software Engineer

We looking for a passionate Principle Engineer - Analytics to build data products that extract valuable business insights for efficiency and customer experience. This role will require managing, processing and analyzing large amounts of raw information and in scalable databases. This will also involve developing unique data structures and writing algorithms for the entirely new set of products. The candidate will be required to have critical thinking and problem-solving skills. The candidates must be experienced with software development with advanced algorithms and must be able to handle large volume of data. Exposure with statistics and machine learning algorithms is a big plus. The candidate should have some exposure to cloud environment, continuous integration and agile scrum processes.

Responsibilities:

• Lead projects both as a principal investigator and project manager, responsible for meeting project requirements on schedule

• Software Development that creates data driven intelligence in the products which deals with Big Data backends

• Exploratory analysis of the data to be able to come up with efficient data structures and algorithms for given requirements

• The system may or may not involve machine learning models and pipelines but will require advanced algorithm development

• Managing, data in large scale data stores (such as NoSQL DBs, time series DBs, Geospatial DBs etc.)

• Creating metrics and evaluation of algorithm for better accuracy and recall

• Ensuring efficient access and usage of data through the means of indexing, clustering etc.

• Collaborate with engineering and product development teams.

Requirements:

• Master’s or Bachelor’s degree in Engineering in one of these domains - Computer Science, Information Technology, Information Systems, or related field from top-tier school

• OR Master’s degree or higher in Statistics, Mathematics, with hands on background in software development.

• Experience of 8 to 10 year with product development, having done algorithmic work

• 5+ years of experience working with large data sets or do large scale quantitative analysis

• Understanding of SaaS based products and services.

• Strong algorithmic problem-solving skills

• Able to mentor and manage team and take responsibilities of team deadline.

Skill set required:

• In depth Knowledge Python programming languages

• Understanding of software architecture and software design

• Must have fully managed a project with a team

• Having worked with Agile project management practices

• Experience with data processing analytics and visualization tools in Python (such as pandas, matplotlib, Scipy, etc.)

• Strong understanding of SQL and querying to NoSQL database (eg. Mongo, Casandra, Redis

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.

What we are looking for:

●       3+ years’ experience developing Big Data & Analytic solutions

●       Experience building data lake solutions leveraging Google Data Products (e.g. Dataproc, AI Building Blocks, Looker, Cloud Data Fusion, Dataprep, etc.), Hive, Spark

●       Experience with relational SQL/No SQL

●       Experience with Spark (Scala/Python/Java) and Kafka

●       Work experience with using Databricks (Data Engineering and Delta Lake components)

●       Experience with source control tools such as GitHub and related dev process

●       Experience with workflow scheduling tools such as Airflow

●       In-depth knowledge of any scalable cloud vendor(GCP preferred)

●       Has a passion for data solutions

●       Strong understanding of data structures and algorithms

●       Strong understanding of solution and technical design

●       Has a strong problem solving and analytical mindset

●       Experience working with Agile Teams.

●       Able to influence and communicate effectively, both verbally and written, with team members and business stakeholders

●       Able to quickly pick up new programming languages, technologies, and frameworks

●       Bachelor’s Degree in computer science

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!

Job Overview

We are looking for a Data Engineer to join our data team to solve data-driven critical

business problems. The hire will be responsible for expanding and optimizing the existing

end-to-end architecture including the data pipeline architecture. The Data Engineer will

collaborate with software developers, database architects, data analysts, data scientists and platform team on data initiatives and will ensure optimal data delivery architecture is

consistent throughout ongoing projects. The right candidate should have hands on in

developing a hybrid set of data-pipelines depending on the business requirements.

Responsibilities

• Develop, construct, test and maintain existing and new data-driven architectures.
• Align architecture with business requirements and provide solutions which fits best
• to solve the business problems.
• Build the infrastructure required for optimal extraction, transformation, and loading
• of data from a wide variety of data sources using SQL and Azure ‘big data’
• technologies.
• Data acquisition from multiple sources across the organization.
• Use programming language and tools efficiently to collate the data.
• Identify ways to improve data reliability, efficiency and quality
• Use data to discover tasks that can be automated.
• Deliver updates to stakeholders based on analytics.
• Set up practices on data reporting and continuous monitoring
  
  

Required Technical Skills

• Graduate in Computer Science or in similar quantitative area
• 1+ years of relevant work experience as a Data Engineer or in a similar role.
• Advanced SQL knowledge, Data-Modelling and experience working with relational
• databases, query authoring (SQL) as well as working familiarity with a variety of
• databases.
• Experience in developing and optimizing ETL pipelines, big data pipelines, and datadriven
• architectures.
• Must have strong big-data core knowledge & experience in programming using Spark - Python/Scala
• Experience with orchestrating tool like Airflow or similar
• Experience with Azure Data Factory is good to have
• Build processes supporting data transformation, data structures, metadata,
• dependency and workload management.
• Experience supporting and working with cross-functional teams in a dynamic
• environment.
• Good understanding of Git workflow, Test-case driven development and using CICD
• is good to have
• Good to have some understanding of Delta tables It would be advantage if the candidate also have below mentioned experience using
• the following software/tools:
• Experience with big data tools: Hadoop, Spark, Hive, etc.
• Experience with relational SQL and NoSQL databases
• Experience with cloud data services
• Experience with object-oriented/object function scripting languages: Python, Scala, etc.

Position: Big Data Engineer

What You'll Do

Punchh is seeking to hire Big Data Engineer at either a senior or tech lead level. Reporting to the Director of Big Data, he/she will play a critical role in leading Punchh’s big data innovations. By leveraging prior industrial experience in big data, he/she will help create cutting-edge data and analytics products for Punchh’s business partners.

This role requires close collaborations with data, engineering, and product organizations. His/her job functions include

• Work with large data sets and implement sophisticated data pipelines with both structured and structured data.
• Collaborate with stakeholders to design scalable solutions.
• Manage and optimize our internal data pipeline that supports marketing, customer success and data science to name a few.
• A technical leader of Punchh’s big data platform that supports AI and BI products.
• Work with infra and operations team to monitor and optimize existing infrastructure 
• Occasional business travels are required.

What You'll Need

• 5+ years of experience as a Big Data engineering professional, developing scalable big data solutions.
• Advanced degree in computer science, engineering or other related fields.
• Demonstrated strength in data modeling, data warehousing and SQL.
• Extensive knowledge with cloud technologies, e.g. AWS and Azure.
• Excellent software engineering background. High familiarity with software development life cycle. Familiarity with GitHub/Airflow.
• Advanced knowledge of big data technologies, such as programming language (Python, Java), relational (Postgres, mysql), NoSQL (Mongodb), Hadoop (EMR) and streaming (Kafka, Spark).
• Strong problem solving skills with demonstrated rigor in building and maintaining a complex data pipeline.
• Exceptional communication skills and ability to articulate a complex concept with thoughtful, actionable recommendations.

The Data Engineer would be responsible for selecting and integrating Big Data tools and frameworks required. Would implement Data Ingestion & ETL/ELT processes

Required Experience, Skills and Qualifications:

• Hands on experience on Big Data tools/technologies like Spark,  Databricks, Map Reduce, Hive, HDFS.
• Expertise and excellent understanding of big data toolset such as Sqoop, Spark-streaming, Kafka, NiFi
• Proficiency in any of the programming language: Python/ Scala/  Java with 4+ years’ experience
• Experience in Cloud infrastructures like MS Azure, Data lake etc
• Good working knowledge in NoSQL DB (Mongo, HBase, Casandra)

Recko Inc. is looking for data engineers to join our kick-ass engineering team. We are looking for smart, dynamic individuals to connect all the pieces of the data ecosystem.

What are we looking for:

1. 3+  years of development experience in at least one of MySQL, Oracle, PostgreSQL or MSSQL and experience in working with Big Data technologies like Big Data frameworks/platforms/data stores like Hadoop, HDFS, Spark, Oozie, Hue, EMR, Scala, Hive, Glue, Kerberos etc.

2. Strong experience setting up data warehouses, data modeling, data wrangling and dataflow architecture on the cloud

3. 2+ experience with public cloud services such as AWS, Azure, or GCP and languages like Java/ Python etc

4. 2+ years of development experience in Amazon Redshift, Google Bigquery or Azure data warehouse platforms preferred

5. Knowledge of statistical analysis tools like R, SAS etc 

6. Familiarity with any data visualization software

7. A growth mindset and passionate about building things from the ground up and most importantly, you should be fun to work with

As a data engineer at Recko, you will:

1. Create and maintain optimal data pipeline architecture,

2. Assemble large, complex data sets that meet functional / non-functional business requirements.

3. Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.

4. 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.

5. Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.

6. Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.

7. Keep our data separated and secure across national boundaries through multiple data centers and AWS regions.

8. Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.

9. Work with data and analytics experts to strive for greater functionality in our data systems.

About Recko: 

Recko was founded in 2017 to organise the world’s transactional information and provide intelligent applications to finance and product teams to make sense of the vast amount of data available. With the proliferation of digital transactions over the past two decades, Enterprises, Banks and Financial institutions are finding it difficult to keep a track on the money flowing across their systems. With the Recko Platform, businesses can build, integrate and adapt innovative and complex financial use cases within the organization and  across external payment ecosystems with agility, confidence and at scale.  . Today, customer-obsessed brands such as Deliveroo, Meesho, Grofers, Dunzo, Acommerce, etc use Recko so their finance teams can optimize resources with automation and prioritize growth over repetitive and time-consuming tasks around day-to-day operations. 

Recko is a Series A funded startup, backed by marquee investors like Vertex Ventures, Prime Venture Partners and Locus Ventures. Traditionally enterprise software is always built around functionality. We believe software is an extension of one’s capability, and it should be delightful and fun to use.

Working at Recko: 

We believe that great companies are built by amazing people. At Recko, We are a group of young Engineers, Product Managers, Analysts and Business folks who are on a mission to bring consumer tech DNA to enterprise fintech applications. The current team at Recko is 60+ members strong with stellar experience across fintech, e-commerce, digital domains at companies like Flipkart, PhonePe, Ola Money, Belong, Razorpay, Grofers, Jio, Oracle etc. We are growing aggressively across verticals.