Top Fintech Data Engineering Jobs

The Complex Data Exchange Specialist manages data integration processes, ensuring high-quality data exchange between clients and systems, while mentoring peers and driving process improvements.

Manage a team of data scientists to develop fraud detection models, lead planning and collaboration with leadership, and communicate outcomes effectively while maintaining strong business intuition and technical leadership.

As a Senior+ Agentic Analytics Engineer, you will design and deploy AI systems that provide actionable insights, build analytics tools, and manage the analytics-to-action pipeline to drive business decision-making using AI.

The Senior Analytics Engineer will design and maintain data models, ensure data quality, collaborate with teams on data requirements, and set engineering standards for data pipelines at Remitly.

The Solutions Architect leads client integration of Cedar's platform, ensuring successful project delivery through client communication and technical expertise while managing complex data structures and operational workflows.

The role involves building scalable data pipelines, optimizing ETL workflows, designing data schemas, and ensuring data quality and governance while collaborating with cross-functional teams.

The Director of Analytics Engineering will lead the strategy and execution of data warehousing and analytics for Current, managing a team and ensuring data integrity.

Design, build, and maintain enterprise ETL/ELT pipelines and data management workflows for market, reference, and financial data in the Markit EDM platform. Implement ingestion, validation, reconciliation, enrichment, monitoring, and distribution processes; support reporting and downstream integrations. Troubleshoot production data issues, collaborate with stakeholders in agile squads, and mentor junior engineers to promote best practices.

The Senior Snowflake Data Engineer designs and optimizes Snowflake architecture and pipelines, ensuring data governance and performance across Marketing and Sales teams.

Curate, cleanse, validate, and maintain large US equity and options datasets; integrate fundamental and alternative data; build data pipelines for research and trading; perform statistical and ML analysis to identify market patterns; document data provenance and collaborate with engineers and traders to deploy production-grade models.