1. Strong SQL Skills: Candidate should be proficient in writing and executing complex SQL queries (no PL/SQL) and be able to handle real-world scenarios confidently.
2. Hands-on Functional Programming (Scala): Strong hands-on experience in Scala is essential.
3. Solid Data Engineering Fundamentals: Emphasis is on strong foundational understanding rather than tool-specific expertise.
4. Experience in Data Quality & Optimization: Candidate should have a sound understanding of data quality practices, performance optimization techniques, and solution design in both event-driven and batch processing contextsincluding data modeling.
5. Sound knowledge in Spark architecture and distributed computing and Spark streaming, including RDD and Data frames core functions, troubleshooting and performance tuning.
6.
Experience in analyzing, re-architecting, and re-platforming on-premises data warehouses to data platforms on any cloud (AWS is preferred)
7. Experience in any cloud (ETL/ELT pipelines, Datalake and Data streaming) is preferred.
8. Understand the client requirement and able to design, develop from scratch and deliver.
9. Able to mentor current members for onboarding to the project.