Top Fintech Data & Analytics Jobs

Lead data and software QA for enterprise data platforms: define testing strategy, build automated test frameworks, validate ETL/ELT and data transformations, run data quality checks and reconciliations, test APIs and data products, analyze datasets with SQL to find defects, drive root-cause resolution, participate in Agile ceremonies, and mentor team members to improve quality practices.

The Senior Data Analyst will analyze complex data sets, provide end-to-end data solutions, and collaborate with stakeholders to drive business decisions.

The Senior Data Analyst will own data models and drive analytical initiatives, ensuring data quality and reliability while providing insights to stakeholders. Responsibilities include managing dashboards and supporting the team with analytics.

Provide reporting and analytics support for the Financial Advisor distribution channel: collect, merge, and analyze large datasets; build dashboards and KPI reports using BI tools; perform ad hoc analyses; automate reporting processes; present findings to stakeholders; and support BI platform users.

The Data Strategy & Sourcing Analyst transforms product data into a strategic asset, ensuring data integrity and driving cost savings through sourcing. Responsibilities include establishing a Single Source of Truth, conducting data analysis, and collaborating with teams for financial impact. The role requires strong analytical skills, proficiency in SQL, and experience with data management tools.

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.

The Senior Reporting & Analytics Consultant leads customer-focused reporting and analytics engagements, developing solutions, supporting implementations, and training clients, while ensuring project success.

Design and implement scalable data models and ETL pipelines (batch and streaming), ensure data quality/SSOT, collaborate with product and platform teams to resolve issues, contribute to data governance, and explore practical integrations between data engineering and AI.

Lead end-to-end analytics engineering: build and maintain BigQuery data warehouse, dbt models, CDC and streaming pipelines (Materialize), orchestration, observability, and BI/analytics products to enable self-service insights and real-time data products.

The Leader of Data Analytics will drive strategic insights from complex data, partnering across functions, ensuring data governance, and leveraging advanced analytics to support HR strategies.