Senior Data Engineer (Python, AWS, AI/ML)

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

Education & Experience

Bachelor’s degree required; Master’s preferred