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Analytics Engineering Manager

Austin, TXNew York, NYSalt Lake City, UTHybrid5+ YOE
Summary

Setpoint is seeking an Analytics Engineering Manager to lead and grow a team of analytics engineers. This player-coach role involves designing and maintaining data pipelines, creating dashboards, and partnering with stakeholders to deliver data products for external customers.

About the role

About the role

Behind many of life’s most important transactions — buying a house, applying for a mortgage, getting a small business loan, or refinancing a credit card — is a network of credit relationships. Setpoint provides critical infrastructure for relationships between the world’s largest banks, credit funds and capital markets counterparties. We’re building trust in this system of credit.

We are looking for an Analytics Engineering Manager to join our team supporting our external data products. In this position you will be reporting into our Head of Analytics and partnering closely with engineering, product, and implementation teams to build and maintain the data infrastructure that powers This is a player-coach role where you’ll lead and grow a team of analytics engineers while staying technically hands-on — designing and maintaining data pipelines, creating dashboards, and working directly with stakeholders to deliver insights that drive business outcomes.

Who will love this job

  • A data product builder – you love creating robust, scalable analytics solutions that drive decision-making.
  • A client partner – you enjoy working directly with clients (asset managers, business owners, technical stakeholders) to understand their needs and deliver solutions that work in the real world.
  • A technical problem solver – you’re fluent in Python, SQL, and DBT, and know how to integrate them into a seamless analytics workflow.
  • A team collaborator – you thrive in cross-functional work with engineering, product, and implementation teams.
  • A strategic thinker – you look beyond the immediate task to anticipate analytics capabilities needed for future growth.
  • A people builder – you get energy from growing engineers and building a high-performing team, not just shipping data products.

What you’ll do

  • Hire, manage, and develop a team of analytics engineers, including performance reviews and career growth.
  • Set technical direction and standards for the analytics engineering team.
  • Mentor engineers and own their professional development.
  • Own end-to-end implementations for the data products for our external customers
  • Build and maintain scalable data pipelines and analytics models using Python, DBT, and SQL.
  • Create and manage dashboards in our external and internal analytics products so stakeholders have actionable insights.
  • Prototype new data products to add to our product suite
  • Collaborate with engineering to drive the roadmap for the data products
  • Use GitHub-based workflows to maintain clean, version-controlled analytics code.
  • Act as a subject matter expert for analytics best practices.

You should have

  • 2+ years of experience managing a team of analytics or related engineering team.
  • 5+ years of experience in analytics engineering, data engineering, or a similar technical role.
  • Proven expertise DBT, SQL, and GitHub-based development. Python is a plus.
  • Strong experience designing, implementing, and maintaining data pipelines and models.
  • Experience in a customer-facing role, working with technical and business stakeholders.
  • Experience working with asset managers, business owners, or financial services data sets is a plus.
  • Excellent problem-solving, communication, and collaboration skills.
  • Must be based in Austin, TX.

Benefits

We offer a comprehensive benefits package that includes competitive salaries, stock options, medical, dental, and vision coverage, 401(k), short term and long term disability coverage, and flexible vacation. We have offices in Austin, TX, New York City, NY, and Salt Lake City, UT with hybrid roles based in these locations and an expectation of two days a week in office (Tuesdays and Thursdays).

Skills
PythonSQLDBTGitHubData PipelinesData ModelingDashboards