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Mid-level metro Data Engineer with broad AWS/ETL requirements and common title increases competition.
Core data engineering skills are transferable, but financial market-data knowledge increases domain specificity.
Explicit 4–7 years plus mandatory Python, SQL and AWS skills enforce moderate shortlisting strictness.
Design, build, and maintain scalable AWS-based ETL/ELT data pipelines and lakehouse platforms for transactional and analytical workloads.
Modernize legacy ETL frameworks to standardized, cloud-native AWS data platforms supporting index construction and analytics.
Implement data quality, governance, and validation frameworks to ensure data accuracy and support financial index calculations.
Bachelor’s Degree in Computer Science, Engineering, Mathematics, or equivalent experience.
4–7 years of experience as a Data Engineer in fintech, trading, market data, or financial analytics preferred.
Strong programming skills in Python and solid SQL expertise; experience with AWS services like S3, Glue, Lambda, Athena/Redshift.
Experience building batch and/or streaming ETL pipelines and working with large, heterogeneous datasets.
Experienced in fintech or financial data engineering environments with domain knowledge of market data and financial instruments.
Skilled in modern cloud-native data architectures, particularly AWS, and capable of transforming legacy ETL systems.
Demonstrated ability to collaborate cross-functionally to translate complex financial logic into scalable data solutions.