Top Financial Services Data Engineering Jobs in CO

Design, build, and own data infrastructure and ETL/ELT pipelines (Airflow, S3, Lambda) into a governed Snowflake warehouse. Implement data quality, IaC (Terraform/CDK), CI/CD, and analytics solutions (SQL, Tableau). Enable ML/LLM use cases like forecasting and anomaly detection and deliver automated reporting and data-driven marketing outputs.

Own and improve the dbt modeling and semantic layers, implement CI/CD, tests, observability, and governance; build governed metrics for BI and AI consumption; partner with Data Engineering and Risk to stabilize pipelines and improve data quality and documentation.

Lead the design and implementation of algorithmic trading strategies, oversee technical infrastructures, and mentor a multidisciplinary team while managing performance analysis and risk.

As a Principal Data Engineer, you'll design and maintain scalable data pipelines and frameworks using Azure technologies while collaborating with various teams to ensure data products support business decisions.

As a Senior Machine Learning Engineer, you'll build and deploy ML models for risk and fraud detection, leading technical efforts and collaborating cross-functionally.

The role involves designing, building, and maintaining ERP data pipelines, ensuring their reliability and supporting data integration initiatives. Responsibilities include troubleshooting, implementing SDLC best practices, and collaborating with stakeholders to optimize data-related outcomes.

Lead Data Engineer responsible for defining architecture, engineering standards, and best practices for the enterprise data platform, collaborating with distributed teams for modernization and scalability.

Design, build, and deploy end-to-end data science solutions for pricing, underwriting, claims, and operations. Perform analyses on structured and unstructured data, develop and monitor ML models, create dashboards and visualizations, implement data pipelines, and collaborate cross-functionally to prioritize analytics initiatives and communicate results to technical and non-technical stakeholders.

The Data Scientist designs and builds data structures for AI applications, manages vector and feature stores, leads data discovery, and collaborates on responsible data use while ensuring high-quality, governed datasets for ML models and applications.

Responsible for designing, developing, and maintaining databases and ETL systems to support business applications and business intelligence. Collaborates with stakeholders to align business requirements and leads the design of automated solutions for operational efficiency.