Job Summary
1. Core Programming
o Python , Scala , Apache Spark (DataFrames, Spark SQL, performance tuning)
o SQL (advanced joins, window functions, query tuning)
o ADO adherence
o Basics of Java – Good to have
2. Data Modeling & Databases
o Data warehousing concepts: star/snowflake schemas, facts & dimensions
o Data modelling & mapping understanding
3. ETL / ELT & Data Pipelines
o Good understanding on ETL & data processing
o Designing batch and streaming pipelines
o Data integration - files, message queues etc
o Hadoop ecosystem (HDFS, Hive) ;Distributed computing concepts (partitioning, shuffling etc)
4. Data Quality & Governance
o Data validation, profiling, and monitoring
o DQ Controls and framework alignment
o Basic knowledge of data governance, security, and compliance controls
5. DevOps & Engineering Practices
o Version control and branching strategies
o Automated builds, tests and deployments; Pipeline-as-code (e.g. YAML-based pipelines)
o Managing artefacts, versioning and rollbacks
6. Production Deployment and Release Management Activities
o Release Planning & Coordination; Code Validation & Post Deployment Checks
o Rollback & Incident Handling
o Continuous Improvement of Release Process
Key Responsibilities
2. To provide client support by presenting data, information, ticket resolution and day to day support activities like monitoring client requirements as well as keeping track of schedule for on time delivery of assigned tasks as per the defined quality standards.
3. To perform activities related to enhancement creation of documents for CMMi and client requirements
4. To provide technical guidance to junior developers
5. To interact with the customer and internal teams to gather requirements for development purposes.