About the RoleWe're a small, high-impact R&D group embedded within a professional hockey organization. Our work directly supports coaches, scouts, and front-office decision makers by turning raw data into tools, models, and insights they can actually use. We build the infrastructure, pipelines, and applications that power better decisions-on and off the ice.
We're looking for a Data Engineer who wants to own meaningful problems end to end, not just write tickets and wait for direction. This is a small team where everyone wears multiple hats, takes initiative, and ships real work. If you like autonomy, creative problem-solving, and hockey, you'll fit right in.
What You'll Do- Design, build, and maintain data pipelines and ETL/ELT workflows using Airflow and dbt to deliver clean, reliable data to analysts and applications.
- Architect and optimize our data warehouse in BigQuery, ensuring data models are performant, well-documented, and built for scale.
- Manage and improve Elasticsearch deployments for search, logging, and analytics use cases.
- Operate within GCP as the primary cloud environment-provisioning infrastructure, managing services, and keeping things running smoothly.
- Collaborate directly with analysts and decision makers to understand what they need and translate that into technical solutions.
- Explore and prototype agentic AI workflows-building intelligent, LLM-driven tools that can automate research, surface insights, or assist in decision support.
- Own projects from ideation through deployment. No hand-offs to a separate team-you see it through.
Required Qualifications- 2-4 years of professional experience in data engineering or a closely related role.
- Strong hands-on experience with BigQuery (or comparable cloud data warehouse) and SQL.
- Proficiency with dbt for data transformation and modeling.
- Experience building and managing workflows in Apache Airflow.
- Working knowledge of Elasticsearch for search, indexing, or observability use cases.
- Solid experience within Google Cloud Platform (GCP). Equivalent experience in AWS or Azure is acceptable, but GCP is our primary environment.
- Proficiency in Python and/or another language commonly used in data engineering.
- Comfort working in a Linux/CLI environment and with version control (Git).
Preferred Qualifications- Demonstrated interest in or experience with agentic AI development-building autonomous or semi-autonomous LLM-based tools, agents, or workflows.
- Familiarity with LLM APIs, prompt engineering, retrieval-augmented generation (RAG), or agent frameworks.
- Interest in or passion for hockey. Understanding the sport, its data, and its culture will make you far more effective and engaged in this role.
- Experience working in a startup-like or small-team environment where resourcefulness matters more than process.
Who You Are- A self-starter. You don't wait for someone to tell you what to do. You identify problems, propose solutions, and move. When something's broken or missing, you fix it or build it.
- An owner. You take full responsibility for your work-from scoping a problem through deploying a solution and keeping it running. You don't punt ambiguity to someone else.
- Creative and resourceful. We're a small group doing a lot with limited resources. You find scrappy, effective solutions rather than waiting for perfect conditions.
- Direct and low-ego. You communicate clearly, give and receive honest feedback, and care more about getting the right answer than being right.
- Curious about hockey. You don't need to be an expert, but genuine interest in the sport and how data can improve it will go a long way on this team.
What We Offer- The chance to directly influence how a professional hockey team makes decisions.
- A small, tight-knit team where your work is visible and valued from day one.
- Autonomy and ownership-real problems, real impact, minimal bureaucracy.
- Exposure to cutting-edge work in agentic AI applied to sports analytics.
- A team culture that values initiative, creativity, and getting things done.
Job Questions:- Are you legally authorized to work in the United States for any employer?
- Please provide your overall compensation requirements.
