Lead Analytics Engineer

ComputerCare has spent more than 20 years building something rare in the IT world: a company where technical excellence and genuine human connection are valued equally. We're the trusted partner that IT leaders turn to when technology can't afford to fail. As a woman-owned business serving innovative companies worldwide, we combine certified technical expertise with a human approach. Whether it's managing complex device lifecycles for global teams or performing authorized repairs for Apple, Lenovo, HP and Dell devices, our work directly impacts how thousands of people stay productive every day. We never outsource our work because we believe in accountability, quality, and building lasting relationships—with our clients and as a team.

If you're passionate about technology, take pride in solving real problems, and want to be part of a company that values both technical excellence and the people behind it, ComputerCare is where you belong.

Come join us in our mission of being the Human Side of Hardware!

We're building our data capabilities and looking for a hands-on Lead Analytics Engineer to take ownership of our data function. As our first dedicated analytics hire, you'll own the pipelines, models, metric definitions, reporting, and data quality that our operations teams and leaders rely on to run the business.

In this role, you'll work closely with leadership and cross-functional teams to turn operational questions into trusted data products, establish consistent definitions for the metrics that matter, and automate reporting that is currently assembled manually.

This is a hands-on builder role, not a people-management role. You'll write SQL, build and operate pipelines, and create models yourself. At the same time, you'll have the autonomy to determine priorities, establish analytics standards, and challenge or clarify requests when the underlying business question or data definition is unclear.

This role is ideal for an experienced analytics professional who is energized by ownership, ambiguity, and the opportunity to build a trusted analytics capability from the ground up.