Remote Senior Data Engineer - Healthcare Analytics

Providence Health & Services; Plainview (TX); Remote; USD 97,000 - 166,000; Full time

Benefits offered by this job

401(k) retirement plan with employer匹配

Health, dental, and vision coverage

Paid parental leave

Job summary

Providence Health & Services is seeking a Senior Data Engineer to analyze clinical data, build data-centric applications, and deliver scalable data pipelines across the health system. You will work with cloud-based platforms to enable analytics for clinical and operational initiatives.

The role emphasizes collaboration with Product, Platform, and Architecture teams, mentoring peers, and advancing data engineering best practices using modern tools and methodologies.

Qualifications

• Bachelor's degree in computer engineering, Computer Science, Mathematics, or Engineering.
• 5+ years of experience as a Senior Data Engineer.
• Masters degree in relevant field is a plus.
• Experience with Hadoop/Spark and NoSQL ecosystems.
• Strong SQL and Python skills for data processing.

Responsibilities

• Analyze clinical data and identify trends to inform care delivery.
• Design and build data-centric software to support clinical and operational workflows.
• Build data pipelines, transformations, and provisioning layers.
• Mentor junior engineers and collaborate with Product, Platform, and Architecture teams.

Skills

SQL

Python

Big data

Hadoop/Spark

NoSQL

HL7/FHIR

APIs

Data modeling

Education

Bachelor's degree

Master's degree (preferred)

Tools

Snowflake

Synapse

Redshift

BigQuery

Airflow

dbt

NiFi

Informatica

Fivetran

FastAPI/Flask

Job description

Providence Health & Services is seeking a Senior Data Engineer to analyze clinical data, build data-centric applications, and deliver scalable data pipelines across the health system. You will work with cloud-based platforms to enable analytics for clinical and operational initiatives.

The role emphasizes collaboration with Product, Platform, and Architecture teams, mentoring peers, and advancing data engineering best practices using modern tools and methodologies.