Data Engineer

We'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., * 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.

• 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)., * 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.