Data Engineer(ETL, SQL, SSIS, Python, AWS)

'Design, build, and maintain scalable data pipelines using SSIS and SQL Server for enterprise data processing.

Develop and optimize Databricks (PySpark / Spark SQL) pipelines for large-scale data transformation and analytics.

Work on batch and near-real-time data ingestion, transformation, and loading (ETL/ELT) across multiple source systems.

Strong hands-on experience with SQL, stored procedures, and performance tuning in SQL Server environments.

Integrate legacy ETL (SSIS) processes with modern cloud-based data platforms (Databricks / Lakehouse architecture).

Experience working with P&C Insurance data domains such as Policy, Claims, Billing, Underwriting, and Loss data.

Understand insurance lifecycle processes and data flows across core insurance systems.

Support data migration and modernization initiatives from on-premise to cloud platforms (Azure/AWS preferred).

Ensure data quality, validation, reconciliation, and governance across all pipelines.

Monitor and troubleshoot ETL jobs, ensuring high availability, reliability, and performance.

Collaborate with business analysts, actuaries, and downstream BI/reporting teams to deliver data solutions.

Work closely with data architects and engineers to define scalable data models and standards.

Implement logging, error handling, and auditing frameworks for data pipelines.

Participate in Agile ceremonies, code reviews, and production deployment activities.

Ensure compliance with insurance regulatory, audit, and data security requirements.