Senior Analytics Engineer: Build Clinical Data Products

ARUP Laboratories

Salt Lake City (UT)

On-site

USD 120,000 - 170,000

Full time

10 hours ago
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Job summary

ARUP Laboratories, a premier clinical and anatomic pathology reference laboratory based in Salt Lake City, Utah, seeks a Sr. Analytics Engineer.

You will model complex clinical and operational data into data products, work with IT, Medical Directors and Lab Managers, and modernize data ontology across clinical domains. Responsibilities include building scalable data pipelines using dbt and orchestrators like Glue/Airflow, and shaping the data platform roadmap for high-volume analytics in a cloud

Qualifications

  • Experience modeling complex clinical/operational data into data products.
  • Ability to architect scalable data pipelines and data lakes/warehouses.
  • Familiarity with modern analytics tooling and cloud workflows.

Responsibilities

  • Apply software engineering best practices to data transformation with dbt and similar frameworks.
  • Architect and optimize query layers for performant analytics across data lake/warehouse.
  • Own ingestion/orchestration frameworks stitching disparate data sources (Glue, Airflow, Dagster).
  • Lead modernization of data ontology for clinical/business domains (Lab Ops, Revenue, Genomics, Quality Control).
  • Contribute to long-term roadmap for scalable cloud storage and compute.

Skills

Data modeling
SQL
Cloud analytics
Cross-functional collaboration
Analytics tooling

Tools

dbt
Airflow
Dagster
Athena
Redshift
BigQuery
Glue

Job description

ARUP Laboratories, a premier clinical and anatomic pathology reference laboratory based in Salt Lake City, Utah, seeks a Sr. Analytics Engineer.

You will model complex clinical and operational data into data products, work with IT, Medical Directors and Lab Managers, and modernize data ontology across clinical domains. Responsibilities include building scalable data pipelines using dbt and orchestrators like Glue/Airflow, and shaping the data platform roadmap for high-volume analytics in a cloud

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