Senior Data Engineer

Design, build, test, deploy, and maintain scalable ETL/ELT data pipelines, data models, and engineering solutions across source systems, data warehouses, and cloud platforms.

Embed automated data quality controls and monitoring within pipelines to ensure reliability and data governance compliance.

Collaborate with cross-functional teams including Data Owners, BI, platform, and governance stakeholders to deliver reusable data assets and support production operations.

Bachelor's degree required; preference for degrees in Computer Science, IT, Data Engineering, Engineering, Mathematics, Statistics, or related quantitative/technology disciplines.

Strong hands-on experience with SQL (joins, aggregations, window functions, stored procedures), Python or equivalent programming, ETL/ELT development, and cloud data platforms.

5 to 8 years of senior-level experience in data engineering involving data transformation, pipeline orchestration, data modelling, and production support.

Experience or familiarity with enterprise tools such as Azure Data Factory, Azure Synapse, Microsoft Fabric, Snowflake, Databricks, Airflow or equivalents is desirable but not mandatory.

Proven ability to implement and optimize scalable data pipelines and data warehousing solutions in global or large enterprise environments, preferably BFSI or consulting sectors.

Experienced in interpreting complex business requirements and source-to-target mappings to technical designs supporting governance and analytics.

Strong ownership ethos, documentation rigor, and collaborative work style across global stakeholder environments.