Top Fintech Data Engineering Jobs

Lead design, implementation, automation, and maintenance of large-scale ETL pipelines and scalable data solutions. Optimize SQL and database performance, collaborate with analytics and business stakeholders to translate needs into data requirements, apply best practices (version control, code reviews, data validation), mentor junior engineers, and ensure delivery of accurate, robust data products while complying with internal policies and regulations.

Build and maintain reliable data pipelines, Airflow DAGs, and Snowflake-based Data Vault/warehouse models. Implement CI/CD, automated testing, observability, and production support while partnering with stakeholders and developing insurance domain expertise.

Design, build, and operate end-to-end data pipelines and curated compliance datasets powering transaction monitoring, KYC/EDD, and screening. Ensure data quality, lineage, and audit readiness; partner with Compliance and Engineering to improve detection signal quality, define metrics, and deliver repeatable reporting and measurement frameworks for control effectiveness.

Maintain and integrate investment data; build data systems and ETL pipelines; analyze large datasets; produce visualizations and reports (Tableau/Power BI/D3.js); improve data quality and governance; develop analytical tools; collaborate with clients, system architects, and product teams.

The Data Migration Specialist optimizes system performance for client data onboarding by utilizing Excel, SQL, VBA, and Python. They resolve data issues, apply accounting concepts, and implement solutions for continuous service improvement, while collaborating with development teams.

Design, implement, and optimize data pipelines and integrations for Multi-Touch Attribution (MTA) marketing analytics. Support client deployments, translate business requirements into technical workflows, maintain data accuracy and performance, and contribute to large-scale, product-driven engagements to drive adoption and measurable business outcomes.

Design, prototype, and deploy analytical and AI-enabled tools integrated with the Aladdin platform to support portfolio construction, research, and decision-making. Work closely with investment teams to identify opportunities, manage projects from ideation to production, and partner with engineering to ensure scalable, reliable solutions.

As a Senior Lead Data Engineer, you'll lead a development team, design and implement data solutions using machine learning, distributed systems, and full-stack technologies, while collaborating with Agile teams and ensuring code quality.

Lead design and deliver cloud-based data engineering solutions across Agile teams. Build, test, and support full-stack data systems using big data, streaming, and cloud technologies; mentor engineers and ensure high-performance, well-tested code.

As a Data Analytics Engineer, you'll build and manage data models in Snowflake, structure datasets for optimal AI performance, and own data transformation while ensuring quality and accessibility for all teams.

Lead the data engineering team, develop and maintain data models and pipelines for risk domains, and manage data quality and governance.

Design, build, and maintain Gusto's data infrastructure and tooling. Handle large-scale batch and real-time data (clickstream, DB, third-party). Own solutions end-to-end: gather requirements, implement pipelines, monitor production, and troubleshoot with stakeholders and cross-functional teams.