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Hoodie Analytics in Chicago (Hybrid) is seeking a hands-on Head of Data Engineering to lead six senior data engineers and shape the data platform. You will write production code weekly, mentor the team, and partner with the founding team to accelerate speed, quality, and scalability as Hoodie grows.
This role blends leadership with deep technical work: architecting the data platform, building with Python, SQL, and Snowflake, and driving AI-assisted engineering practices while balancing cost and
At Hoodie Analytics, data isn't something we use to run the business…it is the business.
Every day, our platform ingests, transforms, enriches, and serves millions of data points that power one of the cannabis industry's leading market intelligence platforms.
We're entering the next stage of our growth, and we're looking for an engineering leader who wants to do more than manage people or own a roadmap. We're looking for someone who believes the best engineering leaders lead by doing; someone who mentors through technical credibility, accelerates the team around them, and still enjoys solving the hardest technical problems themselves while teaching others.
Your mission is simple: increase the speed, quality, and scalability of our engineering organization while continuing to build alongside it.This is a hands-on leadership role. You'll lead a team of six senior Data Engineers, partner directly with the founding team, shape the technical direction of our platform, and continue writing production code every week. As Hoodie grows, you'll help scale both our platform and the engineering organization behind it.
If you're energized by building platforms, growing engineers, and creating high-performing teams that ship exceptional software faster, we'd love to talk.
Lead, coach, and develop a team of six senior Data Engineers while helping shape the next of Hoodie's engineering organization.
Architect and evolve the data platform that powers Hoodie's products.
Build production-grade software using Python, SQL, and Snowflake.
Own the systems that ingest, transform, and serve the data behind our products.
Increase engineering velocity by improving architecture, streamlining technical processes, and thoughtfully leveraging AI and automation where they create meaningful impact.
Improve platform scalability, reliability, observability, and cost efficiency.
Partner with company leadership to establish engineering best practices that enable the team to scale without sacrificing speed or quality.
Mentor engineers through technical leadership, code reviews, architecture discussions, and day-to-day collaboration.
Solve difficult production problems while remaining an active individual contributor.
Experience leading highly technical engineering teams while remaining deeply hands-on.
A background building products where data is the product not simply an internal reporting function.
Strong Python, SQL, and modern cloud data platform experience (Snowflake strongly ).
A proven track record of increasing engineering velocity through better architecture, smarter engineering processes, and modern development practices.
Experience leveraging AI-assisted development and automation to help engineering teams move faster without compromising quality.
Strong architectural judgment that balances scalability, reliability, performance, and cost.
Experience scaling engineering teams within startup or high-growth environments.
The ability to earn trust through technical credibility rather than organizational hierarchy.
You’ll join Hoodie at a pivotal moment.
The platform is proven. Demand is growing. Now we’re investing in the engineering leadership needed to support the next stage of the company’s evolution.
You’ll inherit a talented team, solve meaningful technical challenges, and play a defining role in how engineering operates as Hoodie scales. Every architectural decision you make, every engineer you mentor, and every improvement you introduce will directly impact the products our customers rely on every day.
If you’re excited by building platforms, accelerating engineering teams, solving difficult technical problems, and helping shape the future of a company where data is the product, we’d love to meet you.