Manager, Data Engineering

Responsibilities

• Lead and grow a team of data engineers to support their development, help remove blockers, and foster a collaborative, inclusive team culture.
• Oversee architecture and implementation of our cloud-based data infrastructure (Snowflake, AWS, etc.) to support both operational data delivery and producing consumable data product.
• Partner cross-functionally with Data Science, Product, and Engineering teams to develop high-impact data products and pipelines.
• Drive data engineering best practices across the org-code quality, documentation, testing, observability, and reproducibility.
• Stay close to the work by reviewing code, guiding architectural decisions, and occasionally rolling up your sleeves to code when needed.
• Champion platform scalability by designing systems that handle large volumes of structured and unstructured data with resilience and speed.
• Understand business and operational problems that new tools (Dagster, dbt, etc.) and technology that would improve automation, performance, and data engineering workflows.
• Ensure data reliability and performance by monitoring data pipelines, addressing data quality issues, and driving continuous improvement initiatives.
• Mentor team members and foster technical growth across the group through thoughtful feedback, knowledge sharing, and career coaching.
• Collaborate on strategic planning with leadership-aligning data engineering goals with business objectives.
• Cross team collaboration to share ideas and best practices across teams

Requirements

• 5+ years of experience in data or software engineering, including at least 1-2 years in a people management or team lead role.
• Strong proficiency in SQL and Python-you know when to optimize a query and when to refactor a script.
• Experience designing and supporting modern cloud data platforms (Snowflake, AWS, etc.).
• Deep understanding of ETL architecture, data modeling, and distributed systems.
• Hands-on experience with tools like Dagster, dbt, or similar orchestration/modeling frameworks.
• Familiarity with CI/CD pipelines, infrastructure-as-code, and modern DevOps practices.
• Excellent communication skills-able to bridge technical and non-technical audiences, and to advocate effectively for your team.
• Comfort working in fast-paced, agile environments where priorities may shift and growth is constant.
• Bonus points for experience in healthcare or finance domains, or exposure to machine learning workflows.
• Estimated Salary Range: $131,000 - $164,000
• Find out more about Strata benefits here .
• How we work:
• Our preferred location for open roles is Chicago, IL. We value in‑person connection and regularly host on‑campus events to create meaningful opportunities for our team to build relationships and collaborate
• Thinking about applying?
• Should you require a reasonable accommodation in completing this application, interviewing, completing any pre-employment testing, or otherwise participating in the employee selection process, please reach out to careers@stratadecision.com.
• Here @ Strata...
• Our culture is driven by our people solving problems together. We embrace learning, collaboration, and continuous career growth. Together, we lift our customers, our products, our company, and our community.
• We believe that each of our team member's unique perspectives and experiences is what drives innovation and pos

Benefits

Additional Information

How you'll make an impact: We're looking for a Data Engineering Manager to lead a team of talented data engineers who are passionate about building resilient, scalable data infrastructure that supports some of the nation's top healthcare providers. In this role, you won't just be writing code, you'll also be setting the strategy, coaching your team, and helping to shape how we transform data into insights that help our customers fuel their missions. You'll help us scale our data platform, integrate emerging technologies, and collaborate across departments to ensure our data engineering efforts are aligned, efficient, and forward-looking. If you're energized by mentoring engineers, navigating technical complexity, and improving processes while keeping your hands in the data, we'd love to meet you.

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