Knowledge, Skills, Abilities & Competencies

- Hands-on experience in designing and implementing data platforms, including data warehouses, lakehouse, and contemporary

ETL/ELT pipelines.
- Working knowledge of Microsoft Fabric (Pipelines, Dataflows Gen2, Notebooks, Lakehouse) is strongly preferred.
- Proven ability to build, deploy, and troubleshoot highly reliable, distributed data pipelines integrating structured and unstructured data from various internal systems and external sources.
- Working knowledge of the medallion architecture (bronze/silver/gold) and Delta Lake / OneLake concepts; prior project experience implementing this pattern is highly desirable.
- Solid understanding of data lakehouse patterns and Delta Lake / OneLake concepts, with the ability to structure data models that are AI/ML-ready and support semantic modeling.




- Solid understanding of SQL, relational and dimensional data modeling, query tuning, and basic performance optimization.
- Familiarity with data quality concepts null/duplicate/schema-drift checks, basic SCD handling, and validation rules in transformation pipelines.
- Familiarity with Git, branching strategies, and CI/CD concepts in a data engineering context (Azure DevOps or GitHub

Actions).
- Strong communication and collaboration skills, with the ability to articulate complex data engineering solutions to both technical and non-technical stakeholders, and to lead cross-functional initiatives.

📌 Data Engineer (Bengaluru)
🏢 Careernet
📍 Bengaluru