At Kabam, we’re constantly raising the bar of excellence in free-to-play gaming. We hire for passion and diversity so that we can triumph in our collective skill. Our teams are made up of a fusion of personalities and interests bound together by a collaborative nature, fun-loving culture, and a drive to do what it takes to make great games. And this is where you come in…

The Lead Data Engineer owns Kabam's central data platform end to end, from the game telemetry standard through to the certified data layer that analytics, finance, data science and AI tools are built on. They lead the data engineering team and are accountable for the reliability, quality and cost of petabyte-scale pipelines across GCP and Databricks. They set the standards for how data enters and moves through the platform, and work directly with game, backend and analytics leads to deliver against company priorities.

This role is a full-time, on-site position based 5 days a week at our Downtown Vancouver studio.

In this role, you can expect to:

• Lead and manage the data engineering team: day-to-day direction, performance management, and development.
• Own the data engineering roadmap and prioritise work against company and data priorities.
• Provide technical mentorship and elevate quality through code and architectural reviews.
• Resolve data-definition and implementation questions directly with backend and game leads.
• Define and enforce model contracts, testing and certification so downstream teams can rely on the data.
• Design and evolve the data architecture (lakehouse and medallion layers across GCS, Databricks and BigQuery) for reliability, consistency and efficiency.
• Evaluate and choose technologies and vendors based on value, risk and migration cost.
• Lead platform migrations and modernisation of legacy pipelines.
• Explain architectural decisions and trade-offs clearly to non-technical stakeholders.
• Accountable for data platform spend, including BigQuery and Databricks.
• Identify and deliver cost and efficiency improvements across the data platform, balancing spend against performance and reliability.
• Report cost and efficiency trends to data leadership.
• Build and maintain data pipelines to a high engineering standard using dbt, orchestration tools and devops principles.
• Own data reliability: SLAs, monitoring, incident response, and clear communication of impact and timelines during incidents.
• Identify and prioritise technical debt against delivery work.
• Build data quality monitoring and alerting so issues are caught before stakeholders see them.
• Implement data governance: retention policies, PII and privacy compliance, access control, lineage and documentation.
• Work with data stewards across teams to certify data marts and create high value data assets.
• Collaborate with data scientists on self serve analytics tooling.
• Partner with analytics, core reporting, data science, finance and marketing to turn requirements into data products.
• Manage relationships with external data vendors and partners.
• Proactively identify where better data could add value for teams, and build relationships that encourage data-driven decisions.

To be successful in this role, your background includes:

• Bachelor's degree in a related field, or equivalent experience.
• 7+ years in data engineering, including 2+ years leading engineers or owning a data platform.
• Deep expertise in SQL and Python,