Implement engineering best practices across data pipelines, modeling, data quality, lineage, metadata management, documentation and operational monitoring
Job Summary
Implement engineering best practices across data pipelines, modeling, data quality, lineage, metadata management, documentation and operational monitoring.
Design, architect, develop, and maintain robust and scalable data pipelines, transformations, models, and workflows.
Support Analytics, Operations, and Business teams in data initiatives, deeply understanding functional requirements and delivering data solutions.
Matching Summary
Implement engineering best practices across data pipelines, modeling, data quality, lineage, metadata management, documentation and operational monitoring.
Skills & Requirements
Must-have
SQL, Python, and DBT proficiency
Data modeling and pipeline best practices
Automated QA and data integrity
Cross-functional data engineering support
Nice-to-have
Financial Services background preferred
High-growth technology environments
Work independently and collaboratively
Key Requirements
6+ years of experience in data engineering
Background in Financial Services preferred
Distinguished academic track record
Proven experience building enterprise data platforms
Hands-on experience with data modeling, ETL/ELT pipelines