Cloud Data Engineer (Hybrid) – Pipelines & Analytics

BCBSM, Inc.; United States; Hybrid; USD 61,000 - 98,000; Full time

Benefits offered by this job

Medical, dental, and vision insurance

Life insurance

401k

Paid Time Off (PTO)

Volunteer Paid Time Off (VPTO)

Job summary

Blue Cross and Blue Shield of Minnesota is hiring an Associate Data Engineer to design, build, and support cloud-based data pipelines and data products. You will work with AWS, Databricks, Spark, and Python to enable secure, governed analytics and reporting across the enterprise.

The role emphasizes collaboration with analysts, product owners, and architects, and requires a foundation in data engineering concepts with a willingness to learn and grow within a hybrid work environment.

Qualifications

• 2+ years of related experience or a bachelor's degree in lieu of experience.
• High school diploma (or equivalent).
• Exposure to data engineering concepts, data integration, and analytics engineering.

Responsibilities

• Design, build, and support scalable cloud-based data pipelines and integration solutions.
• Develop data processing, transformation, and quality capabilities using SQL, Spark, Python, and cloud services.
• Collaborate with stakeholders to translate data requirements into technical tasks and deliverables.
• Contribute to engineering standards, reusable patterns, and continuous improvement.

Skills

SQL fundamentals

Python

Problem solving

Strong communication

Curiosity

Willingness to learn

Time management

Education

Bachelor's degree in related field

High school diploma or equivalent

Tools

Databricks

Apache Spark / Spark SQL

Delta Lake

AWS

Terraform (IaC)

GitLab / GitHub Actions / Jenkins

Job description

Blue Cross and Blue Shield of Minnesota is hiring an Associate Data Engineer to design, build, and support cloud-based data pipelines and data products. You will work with AWS, Databricks, Spark, and Python to enable secure, governed analytics and reporting across the enterprise.

The role emphasizes collaboration with analysts, product owners, and architects, and requires a foundation in data engineering concepts with a willingness to learn and grow within a hybrid work environment.