Associate Data Engineer

bcbsmn; Eagan (MN); On-site; USD 80,000 - 110,000; Full time

Job summary

Blue Cross and Blue Shield of Minnesota is seeking an Associate Data Engineer to design, build, and support scalable data pipelines in a cloud-first environment. You will collaborate with application engineers, analysts, and business stakeholders to deliver secure and governed data solutions.

The role emphasizes building data integration patterns, event-driven workflows, and data transformation capabilities with Python, SQL, and Spark in modern enterprise data platforms.

Qualifications

• 2+ years related experience or bachelor's degree in lieu of experience.
• High school diploma (or equivalent)

Responsibilities

• Design, build, and support scalable cloud-based data pipelines and integration solutions.
• Develop and maintain data processing, transformation, and quality capabilities using AWS, Databricks, SQL, Spark, and Python.
• Partner with business and technical teams to translate data requirements into solutions, troubleshoot issues, improve platform performance.

Skills

Python

SQL

Databricks

Apache Spark

Delta Lake

Communication skills

Curiosity

Willingness to learn

Time management

Problem-solving

Education

Bachelor's degree or equivalent

Tools

Databricks

Apache Spark

Delta Lake

Job description

About Blue Cross and Blue Shield of Minnesota

At Blue Cross and Blue Shield of Minnesota, we are committed to paving the way for everyone to achieve their healthiest life. We are looking for dedicated and motivated individuals who share our vision of transforming healthcare. As a Blue Cross associate, you are joining a culture that is built on values of succeeding together, finding a better way, and doing the right thing. If you are ready to make a difference, join us.

The Impact You’ll Have

The Associate Data Engineer supports the design, development, delivery, and ongoing support of enterprise data products, data integration solutions, and cloud-native data platforms. The role works with structured and unstructured data to help enable analytics, operational reporting, interoperability, and digital business capabilities through reliable data engineering solutions.

This position focuses on building and maintaining modern data pipelines, cloud-native integration patterns, event-driven workflows, and data transformation capabilities under the guidance of senior engineers and architects. The Associate Data Engineer collaborates with application engineers, product owners, analysts, and business stakeholders to deliver secure, governed, and scalable data solutions.

The ideal candidate brings foundational experience with data engineering concepts, SQL, Python, cloud data platforms, and distributed processing technologies, with a strong willingness to learn and grow in modern enterprise data engineering practices.

What You’ll Do

Design, build, and support scalable cloud-based data pipelines and integration solutions that enable secure, reliable, and efficient data movement across enterprise systems.

Develop and maintain data processing, transformation, and quality capabilities using technologies such as AWS, Databricks, SQL, Spark, and Python, while following best practices for security, governance, testing, and DevOps.

Partner with business and technical teams to translate data requirements into solutions, troubleshoot issues, improve platform performance, and contribute to engineering standards, reusable frameworks, and continuous innovation.

How You’ll Do It

Core Responsibilities

• Develop, deploy, and support data pipelines, integration solutions, and data products that support enterprise business capabilities.
• Assist with implementation of cloud-native data processing solutions using AWS services, Databricks, and distributed data processing frameworks.
• Develop and support batch, API, file-based, and event-driven integration patterns that enable secure and reliable data exchange.
• Contribute to technical design activities for data engineering solutions, including data models, transformation logic, ingestion patterns, and consumption layers.
• Develop and test data transformation logic using SQL, Spark, Python, and related technologies.
• Build and support data ingestion, enrichment, quality, lineage, and observability capabilities that improve trust, transparency, and operational supportability.
• Support CI/CD pipelines, infrastructure automation, testing strategies, and DevOps practices for data platforms and data products.
• Partner with business stakeholders, application teams, and architects to understand requirements and translate them into technical tasks and deliverables.
• Follow enterprise standards for security, governance, reliability, performance, and maintainability.
• Troubleshoot data processing and integration issues while contributing to improvements in platform performance, resiliency, and operational efficiency.
• Contribute to engineering standards, reusable patterns, documentation, and team best practices.

Additional Responsibilities

• Participate in technology evaluations, proof-of-concept initiatives, and architecture reviews as directed.
• Contribute to reusable integration, transformation, and data platform patterns.
• Share knowledge through documentation and team learning activities.
• Stay current on cloud, data engineering, AI, and interoperability technologies relevant to the role.

Required Skills & Experience

• 2+ years related experience or bachelor's degree in lieu of experience.
• High school diploma (or equivalent)

Preferred Skills & Experience

Skillset and Experience

• Related technical, professional, internship, academic, or project experience. All relevant experience including work, education, transferable skills, and military experience will be considered.
• Exposure to data engineering, data integration, software development, analytics engineering, or data platform development.
• Essential Candidate Qualities: Curiosity, willingness to learn, problem-solving mindset, strong communication skills, self-motivation, and time management skills.

Data Engineering & Analytics

• Exposure to Databricks or similar cloud data platforms
• Exposure to Apache Spark / Spark SQL
• Familiarity with Delta Lake or similar storage formats
• Python
• SQL
• Foundational understanding of data modeling and schema design
• Famil