We are seeking a Senior Data Engineer with strong Python expertise to design and deliver scalable ETL solutions supporting enterprise analytics and financial/insurance data platforms. This role focuses on building reliable, secure data pipelines using AWS Glue and modern data engineering practices in a hybrid, day‑shift work model.
Responsibilities
* Design and develop scalable Python‑based ETL pipelines, primarily using AWS Glue
* Build and optimize ETL jobs to process large volumes of structured and semi‑structured data
* Apply performance tuning, partitioning, and monitoring to meet SLA and reliability goals
* Implement data quality checks, validation rules, and error handling
* Integrate data pipelines with S3, Athena, Lambda, and analytics platforms
* Ensure secure data handling in compliance with regulatory and enterprise standards
* Partner with architects, analysts, and product owners to translate business requirements into data solutions
* Support production workloads, troubleshooting, and continuous improvement
* Follow software engineering best practices including CI/CD, code reviews, and documentation
Required Qualifications
* Strong hands‑on experience with Python in production environments
* Proven background in ETL and data pipeline development (Spark‑based preferred)
* Experience with AWS data services (Glue, S3, Athena, CloudWatch) or equivalent platforms
* Solid SQL and data modeling skills
* Experience working in agile, hybrid delivery environments
Nice to Have
* Experience in financial services or insurance data
* Exposure to advanced data processing (documents, semi‑structured data, data enrichment)
* Familiarity with ML‑enabled data pipelines or model integration
* AWS or cloud data engineering certifications
Bachelor’s degree required; Master’s preferred
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