Data Engineer (AI/ML)

Blue Cross Blue Shield Association (BCBSA)

Quick summary

Work type: On-site
Location: Chicago, IL
Salary: $100,800–$138,600 / yr
Posted: 3 days ago
Nearby: 99+ roles within 25 mi

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $168k

This role $120k

$88k most similar roles pay here $224k

This role pays less than 91% of similar roles. Most pay $126,800–$209,750 — the shaded band above. At the midpoint, this role pays about $120k versus about $168k for comparable roles.

Based on 240 similar postings.

Employer

About Blue Cross Blue Shield Association (BCBSA)

The Blue Cross Blue Shield Association is a federation of 33 independent health insurance companies providing health coverage to millions of Americans through locally operated member plans. Industry: Health Insurance

Blue Cross Blue Shield Association (BCBSA) currently has 4 open roles on FindRole.

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View all roles at Blue Cross Blue Shield Association (BCBSA)

At a glance

TL;DR · Data Engineer (AI/ML)

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The Data Engineer will join the Machine Learning and Generative AI team as a senior member, focusing on designing and maintaining scalable data pipelines for healthcare applications using PySpark, Databricks, AWS Glue, EMR, and Snowflake. Day-to-day responsibilities include transforming unstructured healthcare data into actionable insights, collaborating with Data Architects to ensure compliance with HIPAA and SOC 2 standards, and optimizing cloud-based systems for cost efficiency. The role requires hands-on experience with workflow orchestration tools like Airflow and Kubernetes, proficiency in Python and SQL, and familiarity with AWS AI/ML services such as SageMaker and Bedrock. Ideal candidates will have a background in healthcare data management and a passion for contributing to innovative solutions that support the growing needs of the healthcare industry.

Skills

AWS PySpark Databricks Snowflake Kubernetes Airflow Python SQL Amazon_SageMaker Amazon_Glue Amazon_EMR NoSQL relational_databases CI/CD SOC_2 HIPAA GDPR PostgreSQL Terraform

What you'll do

Design and build scalable data pipelines for ML and GenAI using PySpark and cloud tools.
Ensure compliance with healthcare standards (HIPAA) in data engineering practices.
Collaborate on architecture decisions to support machine learning and generative AI workloads.
Implement and maintain data validation frameworks to ensure pipeline accuracy and completeness.
Participate in performance tuning, cost optimization, and scaling strategies for cloud-based systems.

What we're looking for

5+ years of experience in data engineering with cloud-based environments.
Hands-on expertise with AWS AI/ML services like SageMaker, Glue, EMR, and Databricks.
Experience designing and optimizing data architectures for ML and GenAI workloads.
Proficiency in Python, SQL, and distributed data frameworks (PySpark, Airflow).
Knowledge of healthcare standards (HIPAA, HL7, FHIR) and compliance frameworks.

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