Responsibilities :

- Actively participate in the design, implementation, and continuous improvement of end-to-end data platform architecture using modern Azure cloud technologies including Azure Data Factory, Azure Data Lake Storage, and Microsoft Fabric (Lakehouses and Warehouses).

- Build scalable, reliable ELT/ETL pipelines to ingest, process, and transform data from multiple source systems including GCAS, GSS, Insurance, Savvy, and BAS systems.

- Implement and maintain automated data quality checks and pipeline testing to ensure reliability and trust.

- Develop and maintain data lakehouse solutions implementing medallion architecture patterns with bronze, silver, and gold layers for progressive data refinement.

- Collaborate with offshore data engineering partners to deliver data engineering initiatives, providing technical guidance and ensuring quality standards.

- Assist the Business Intelligence team with reporting and analytics requirements, ensuring their needs are supported through effective data solutions.

- Contribute to and adhere to established data governance and security practices, including metadata management, data quality frameworks, and data cataloging, to promote trust and reliability.

- Enable business functions with clean, structured data that supports compliance reporting, customer insights, fraud detection, and product development.

- Provide detailed documentation, knowledge transfer, and training to internal teams to build data literacy.

Tech Stack :

- Snowflake, Azure Data Factory (ADF), Azure Data Lake Storage (ADLS Gen2), Microsoft Fabric, dbt, Python, SQL, Looker, Git, CI/CD.