Senior Cloud Data Engineer

Job summary

University Staff Description Uni*** 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.

Benefits

Qualifications

• 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:
• The Linda Crnic Institute for Down Syndrome (www.crnicinstitute.org) is the largest academic home for Down syndrome research.
• The Crnic Institute collaborates with prominent scientists and leaders around the globe to enable precision medicine approaches to improve health outcomes in Down syndrome.
• The Crnic Institute is seeking a detail-oriented, highly motivated, and enthusiastic full-time Senior Data Cloud Engineer to work as a member of our Information Technology team.
• Why work for the University?
• We have AMAZING
• Minimum

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

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Contract length