Experience Required: 6+ Years
Key Responsibility:
- Design and implement modern data lakehouse architectures (Delta Lake, or equivalent) on cloud platforms like AWS, Azure, or GCP.
- Define data modeling, schema evolution, partitioning, and governance strategies for high-performance and secure data access.
- Own the technical roadmap for scalable data platform solutions, aligned with enterprise needs and future growth.
- Provide architectural guidance and code/design reviews across data engineering teams.
- Build and maintain reliable, high-throughput data pipelines for ingestion, transformation, and integration of structured, semi-structured, and unstructured data.
- Solid understanding of data warehousing concepts, ETL/ELT pipelines, and data modeling
- Experience with tools like Apache Spark (PySpark/Scala), Hive, DBT, and SQL for large-scale data transformation.
- Design ETL/ELT workflows using orchestration tools like Apache Airflow, Temporal, or Apache NiFi.
- Lead and mentor a team of data engineers and provide guidance on code quality, design principles, and best practices.
- Act as a data architecture SME, collaborate with DevOps, Data Scientists, Product Owners, and Business Analysts to understand data requirements and deliver aligned solutions.
