Data Analytics Engineer

IsoTalent • Full-time • Salt Lake City Metropolitan Area, US • $130k - $150k / year • 6d ago

Data Analytics Engineer

Location: Onsite – Salt Lake City, UT

About the Role

Our client, a mission-driven organization in the healthcare research space, is seeking a Data Analytics Engineer to join their growing data and technology team! Do you have expert-level SQL and Python skills and a passion for transforming healthcare data into actionable insights? Are you excited about building scalable analytics pipelines that directly support real-world research and patient outcomes? If so, this could be the perfect opportunity for you.

The Perks

Compensation: $130,000–$150,000, based on experience
Benefits: Health & Dental Insurance, Unlimited PTO
Perks: Collaborative, mission-driven culture; flexible work environment; meaningful work alongside researchers and patient advocates

A Day in the Life of the Data Analytics Engineer

As a Data Analytics Engineer, you’ll design, build, and optimize modern data systems that power cutting-edge healthcare research. You’ll use your SQL and Python expertise to develop pipelines, integrate healthcare data sources, and enable analytics for clinicians and researchers focused on improving patient outcomes.

Responsibilities include:

Designing, developing, and maintaining cloud-based data infrastructure (BigQuery, Firestore, GCP)
Writing advanced SQL queries for transformation, validation, and performance optimization
Developing Python scripts and automation workflows to streamline ingestion, transformation, and analytics
Building and managing dbt models to support scalable data pipelines
Integrating diverse healthcare datasets (EHR, FHIR, OMOP, claims, patient-reported outcomes) into unified systems
Ensuring data quality, validation, and reproducibility throughout all workflows
Collaborating with analysts, researchers, and product teams to build actionable dashboards and insights
Continuously improving data reliability, performance, and scalability

Requirements and Qualifications

Bachelor’s degree in Data Science, Computer Science, Statistics, or related field (or equivalent experience)
5+ years of experience in data engineering, analytics engineering, or applied data science
Advanced proficiency in SQL and Python (must-have; daily-use level)
Experience developing and maintaining dbt models, ETL/ELT pipelines, and cloud-based data systems (BigQuery, Firestore, or similar)
Familiarity with healthcare data formats and standards (FHIR, OMOP, EHR, claims)
Experience automating workflows and data validation processes
Strong collaboration and communication skills with cross-functional teams
Passion for using data to improve real-world healthcare outcomes

About the Company

Our client is redefining how healthcare data is used to drive real-world research, improve treatment outcomes, and empower patients. They’re at the forefront of building scalable data systems that integrate AI, patient-reported data, and clinical insights to revolutionize precision medicine.