Top Fintech Data Engineering Jobs

As a Senior Associate in Data Analytics Engineering, you will enhance data analytics capabilities, develop internal analytics solutions, and collaborate with various teams for data utilization. You will also establish analytics standards and champion self-service data initiatives while providing cross-organizational support.

The Staff Analytics Engineer will own the Financial Subledger Data Platform, build dbt models, implement data quality controls, and mentor a junior engineer, ensuring high operational reliability and cross-functional collaboration.

The Solutions Data Engineer will manage data integrations end-to-end, utilizing FloQast's Data Platform and Data Studio to connect source systems and transform data for reliable outputs across applications.

Lead data infrastructure and business systems including Salesforce, Okta, ETL, and BI tools. Build analytics/reporting (ARR, renewal schedules, cohort analysis), manage data pipelines and integrations, oversee IT admin across offices, and deliver product and GTM analytics to inform leadership decisions.

The Head of Data will shape the data architecture, manage data infrastructure, and facilitate insights through self-serve analytics while collaborating with AI teams.

The Assistant Vice President collaborates with stakeholders to design and optimize data reports, manages database systems, and develops ETL processes for data warehousing, supporting production issues and enhancements using various tools.

The role requires designing, building, and maintaining data pipelines using Big Data technologies. Responsibilities include developing ETL processes, ensuring data integrity, collaborating with teams, and applying AI techniques to drive efficiency.

The Customer Data Engineer will design, maintain, and optimize data models for the Customer Data Platform, ensuring high-quality data integration and analytics. Responsibilities include building SQL queries, managing data structures, and supporting analytics with a focus on data quality.

The role involves enhancing actuarial systems using AI, gathering requirements, translating complex concepts, collaborating with technical teams, and promoting responsible AI usage.

The Senior Data Engineer will design and maintain scalable ETL/ELT pipelines, develop data models, ensure data quality, and collaborate with cross-functional teams to drive analytics and machine learning operations.