Data Integration Engineer

Job description

PFB Skills Required ETL, Informatica, PLSQL with Cloud Exposure(AWS/IICS/Azure) Grade – G5/G6 Location – Chennai and Bangalore **Hands-on coding expertise in PL/SQL, Informatica ETL, SQL, Data Integration, and Data Modelling**, with any exposure to Cloud platform. Begin with a practical retail sales scenario and ask the candidate to design a database schema, create tables with appropriate keys and constraints, and write SQL queries involving joins, aggregations, subqueries, CTEs, window functions, and data reconciliation. Evaluate their ability to develop and optimise **PL/SQL Stored Procedures, Functions, Packages, Triggers, Views, Exception Handling, Cursors, and Bulk Processing**, including real-world use cases. Assess **Informatica ETL** expertise by asking the candidate to design source-to-target mappings and explain the use of transformations such as Lookup, Joiner, Aggregator, Expression, Router, Update Strategy, and Sequence Generator. Evaluate their experience with workflows, sessions, parameter files, reusable components, error handling, restartability, performance tuning, and SCD Type 1/2 implementations. Review their approach to ingesting, cleansing, transforming, validating, and reconciling data from multiple sources. Assess how they handle duplicate records, rejected rows, failed loads, late-arriving data, audit controls, and data quality checks. Evaluate **Data Modelling** skills by asking the candidate to design a Star Schema with Fact and Dimension tables, define grain, identify measures, and explain surrogate keys and dimensional modelling best practices. Assess database administration and optimisation knowledge, including indexing, partitioning, execution plans, query tuning, permissions, roles, and troubleshooting slow-running SQL queries and ETL jobs. Verify exposure to **Cloud platforms (AWS/Azure/GCP)** and Snowflake. Discuss services such as S3, RDS, EC2, Redshift, Glue, or equivalent cloud services, along with Snowflake concepts including Virtual Warehouses, Stages, Snowpipe, Streams, Tasks, Time Travel, and Data Sharing. Finally, assess problem-solving capabilities through production support scenarios involving ETL failures, PL/SQL performance issues, reconciliation mismatches, data quality concerns, and cloud data pipeline incidents. Focus on **practical implementation, coding proficiency, optimisation techniques, troubleshooting approach, and real project experience rather than theoretical knowledge**.