Senior Analytics Engineer

About the role

The Sr. Analytics Engineer is responsible for modeling complex clinical and operational data into data products that capture how a world-class laboratory functions. They work with IT staff, medical directors, and lab managers to understand the nuances of laboratory operations to augment the data model for modern analytics tooling.

Responsibilities

• Apply software engineering best practices to the data transformation layer using industry-standard frameworks like dbt.
• Architect and optimize the query layer to ensure performant analytics across the data lake and warehouse using serverless or managed technologies like Athena, Redshift, or BigQuery.
• Own the ingestion and orchestration frameworks that stitch together disparate clinical data sources using modern tools like Glue, Airflow, or Dagster.
• Lead the modernization of ARUP’s data ontology for specific clinical and business domains such as Laboratory Operations, Revenue Cycle, Genomics, and Quality Control.
• Contribute to the long-term technical roadmap for the data platform, informing high-level decisions on how to scale cloud-based storage and compute to handle high-volume data.
• Collaborate with leadership to collect requirements and write the code for Secure, Timely, Accurate, Trusted, and Extensible (STATE) data products.

Requirements

• Experience with software engineering best practices (version control, modularity, and automated testing).
• Knowledge of industry-standard frameworks such as dbt.
• Experience with serverless or managed technologies like Athena, Redshift, or BigQuery.
• Experience with modern tools such as Glue, Airflow, or Dagster.
• Experience leading the modernization of data ontologies for specific clinical and business domains.
• Experience contributing to the long-term technical roadmap for data platforms.
• Experience collaborating with leadership to collect requirements and write code for STATE data products.

Qualifications

• Bachelor’s degree in Computer Science, Data Science, or related field.
• Minimum of 5 years of relevant experience in data engineering or similar field.
• Strong understanding of data modeling, database design, and data warehousing principles.
• Experience with data transformation and ETL processes.
• Experience with cloud-based storage and compute solutions.
• Experience with modern data processing tools and techniques.
• Experience with version control systems and automation tools.
• Experience with data security and compliance standards.

Skills

• Software engineering best practices.
• Industry-standard frameworks like dbt.
• Serverless or managed technologies like Athena, Redshift, or BigQuery.
• Modern tools like Glue, Airflow, or Dagster.
• Data modeling and database design.
• Data warehousing principles.
• Data transformation and ETL processes.
• Cloud-based storage and compute solutions.
• Modern data processing tools and techniques.
• Version control systems and automation tools.
• Data security and compliance standards.

Benefits

ARUP offers a comprehensive benefits package including health insurance, retirement plans, paid time off, and more. The company also provides opportunities for professional development and growth within the organization.

Pay

$XX.XX - $XXXX per year based on experience and qualifications.

Schedule

Monday - Friday (40 hrs/wk) 8:00 AM - 5:00 PM