Top Financial Services Data Engineering Jobs in CO

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.

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

The Data Platform Engineer II role involves automating data infrastructure, scaling analytics platforms, and ensuring system reliability and security. Key responsibilities include managing CI/CD pipelines, configuring secure networking, and collaborating with Data & Analytics teams to optimize performance.

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.

Manage client-facing data and analytics projects: define data strategy, build automation and ETL, develop visualizations and predictive analytics, drive transformation, manage scope/budget, and communicate findings to non-technical stakeholders while leveraging finance knowledge.

Lead design and maintenance of scalable data models, dbt transformations, and cloud data warehouses. Manage a distributed team of 7–8 data engineers/analysts, ensure data quality, governance, ELT best practices, performance tuning, integrations, and stakeholder alignment across servicing technology.

Lead architecture and scaling of the Databricks data warehouse and self-service data platform. Build reusable batch and streaming frameworks, enforce governance, SLOs, lineage, observability, CI/CD, and multi-tenancy. Mentor engineers, run design reviews, and ship documented patterns to enable analytics, data science, and app teams to move quickly without blocking on platform tickets.

Lead and mentor data engineering teams to ensure 24x7 platform stability, resiliency, and performance. Drive modernization to cloud-native lakehouse and event-driven architectures, implement AI-driven automation and observability, define SLAs/SLOs, reduce MTTD/MTTR, and standardize CI/CD and SRE practices to enable reliable analytics, regulatory reporting, and downstream AI/ML use cases.

Implement and maintain ETL processes to ingest and transform hospital data into Meduit platforms. Build data models, ensure data integrity, document and track tasks in Jira, collaborate with cross-functional teams, support revenue-cycle data implementations, and mentor team members on best practices.