Top Fintech Data Engineering Jobs

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

Assist in developing, testing, and maintaining software applications, collaborate on designs, participate in code reviews, and contribute to documenting processes.

Summer internship on the Data & Analytics Platform team building automation, model prototypes, and platform features. Work with engineers to write, test, and deploy code, partner with internal customers to prototype ML and generative workflows, and participate in design discussions and code reviews in an agile environment.

Lead Analytics Engineer responsible for data modeling, transformation, pipeline orchestration, quality governance, and empowering data-driven decisions across the organization.

Design, build, and maintain scalable data pipelines integrating diverse sources into analytics platforms. Own projects, standardize pipeline tooling, implement automated data tests, ensure security/PII handling, support on-call troubleshooting, and mentor team members to enable reliable, production-grade data delivery.

Lead the development and implementation of automation techniques using AI and machine learning to improve life underwriting operations and processes.

The Senior Analytics Engineer will design data models, build data pipelines, and support analytics needs across teams, enhancing data infrastructure.

The Data Platform Engineer will architect and build a foundational data platform for AI, managing ingestion systems, data quality, and mentorship while working with diverse data types and technologies.

The Data Engineer will build real-time data pipelines for pricing algorithms, collaborate with teams, and contribute to batch data workflows.

Lead the data strategy, architecture, and design initiatives across payments services, reconciliations, and reporting by simplifying data pipelines and enhancing analytics.

The role involves developing and optimizing big data applications, collaborating with users, managing the development process, and mentoring less experienced analysts while ensuring compliance with regulations.