Data Engineer- Python/Pyspark Developer

Direct Responsibilities

• Design & develop robust ingestion, transformation, and enrichment pipelines with Python, PySpark, and SQL.
• Write and optimize complex SQL queries, analytical UDFs, and window functions for data aggregation and reporting.
• Collaborate with CEFS data architects, data scientists, and business analysts to translate functional requirements into technical specifications.
• Unit test, integrate test, and review code.
• Maintain CI/CD pipelines (Git, Jenkins, Docker) for automated build, test, and deployment of jobs.
• Monitor production workloads and troubleshoot performance bottlenecks, memory issues, and job failures.
• Document data lineage, pipeline design, and operational run books in Confluence/SharePoint.
• Keep up to date with latest technologies and trends and provide input, expertise and recommendations.

Contributing Responsibilities

• Contribute towards innovation (e.g. AI/ML); suggest new technical practices for efficiency improvement.
• Participate in Agile ceremonies (sprint planning, daily standups, retrospectives) and help groom the backlogs.
• Mentor junior engineers and champion best practices in Python coding, Spark optimization, and data engineering patterns.
• Evaluate emerging technologies and deliver proof of concepts for CEFS.

Technical & Behavioral Competencies

• Resourceful to quickly understand complexities involved and provide the way forward.
• Good experience in technical analysis of n-tier applications with multiple integrations using object oriented, APIs & Microservices approaches.
• Strong knowledge about design patterns and development principles.
• Inclination and prior experience of working across SQL, Python and ETL.
• Strong Hands-on experience - Python (NumPy, pandas, Python Frameworks, Restful APIs, MS-SQL or Oracle.
• PySpark - DataFrames, Spark SQL, Structured Streaming, performance tuning (partitioning, caching, broadcast joins).
• Advanced SQL complex queries, stored procedures, query optimization.
• Good Knowledge and experience to use Python packages such as Pandas, NumPy, etc. for cleaning up of Data, Data Wrangling, Analysis of Data and Visualization of Data.
• Good experience in development and maintenance of code/scripts in both functional and technical specifications of all applications component, bug fixing and production support.
• Good knowledge on Linux/Unix environment (basic commands, shell scripting, etc.), testing phases, documentation and new framework.
• Some experience of working with build tools like Maven & DevOps tools like Bitbucket, Jenkins.
• Knowledge of Agile, Scrum, DevOps.
• Development experience in Data Engineering environment.
• Ability & willingness to learn & work on diverse technologies (languages, frameworks, and tools).