Data Engineer
This role is critical in establishing the foundation for reliable, secure, and high-performing data systems that enable analytics, applications, and strategic decision-making across the organization.
University of Colorado Anschutz Medical Campus
Department: School of Medicine
Job Title: Senior Cloud Data Engineer
Position #: 00850335 – Requisition #: 40490
Job Summary:
We are seeking a Senior Cloud Data Engineer to design, build, and scale our core data platform, including data warehouse and data lakehouse environments. This role is critical in establishing the foundation for reliable, secure, and high-performing data systems that enable analytics, applications, and strategic decision-making across the organization.
This is a highly hands-on individual contributor role suited for someone who thrives in a fast-paced, evolving environment, is comfortable navigating ambiguity, and can take ownership of complex data challenges from design through implementation within a small, agile team.
Key Responsibilities:
25% - Design, develop, and evolve cloud-based data warehouse and lakehouse architectures.
25% - Architect and implement scalable data pipelines and integration frameworks, core data integrations, ETL/ELT pipelines using Python and SQL across a wide range of data sources, including:
Ingesting transactional data from PostgreSQL and other relational systems.
Processing large-scale data exports & file-based ingestion (e.g., S3, Azure Blob, SFTP, etc.) and mastering data into unified analytical models.
Supporting interoperability through healthcare integrations using FHIR protocols.
Integrating specialized systems such as medical record curation platforms into centralized data environments.
RESTful APIs.
Application backends.
20% - Design and deliver data products, curated datasets, and analytical data models, transforming normalized (3NF) source data into performant, analytics-ready structures (e.g., star/snowflake schemas).
10% - Optimize storage and processing strategies within lakehouse environments (e.g., Parquet, partitioning, efficient query design).
5% - Establish and follow best practices for data quality, reliability, observability, and performance.
5% - Collaborate with stakeholders to define and deliver solutions in situations where requirements may be ambiguous, incomplete, or rapidly evolving.
5% - Contribute to and maintain CI/CD pipelines and DevOps practices for data engineering, including automation and deployment strategies.
5% - Participate in Agile workflows using Jira, contributing to backlog refinement, sprint planning, and delivery execution.
Work Location:
Remote – this role is eligible to work remotely, but the employee must be in the United States.
Why Join Us:
Posted July 24, 2026