Data Engineer (TubeBuddy)

GameSquare Holdings Inc. is a cutting-edge media, entertainment, and technology company transforming how brands and publishers connect with Gen Z, Gen Alpha, and Millennial audiences. They are seeking a Data Engineer to build and operate TubeBuddy’s ETL/ELT pipelines and lakehouse/warehouse models, ensuring data quality and collaborating with cross-functional teams.

Responsibilities:

• Design, build, and maintain ETL/ELT batch pipelines landing raw data into our S3 data lake and promoting curated datasets into Databricks
• Implement reliable backfills and reprocessing workflows to keep historical data correct
• Build and maintain dbt models (staging through marts) with clean layering, documentation, and automated tests
• Partner with stakeholders to define canonical metrics and ensure consistent definitions across reporting
• Own data quality expectations (freshness, completeness, and correctness) for core datasets
• Partner with Engineering, Product, and Analytics to deliver high-quality datasets for reporting, experimentation, and analysis
• Support product analytics event data in the warehouse (Segment → Databricks), including identity/joins and schema stability
• Contribute to product-facing engineering work when needed, including light backend and application development support

Requirements:

• 3–5+ years of data engineering experience shipping production pipelines
• Bachelor's degree, or Master's degree in computer science, statistics, information systems, or a related, technical field
• Strong programming experience with Python and SQL
• Hands-on experience with cloud storage and lakehouse/warehouse patterns (we use S3 and Databricks)
• Strong experience with dbt for transformations, testing, and documentation
• Proven ability to operate pipelines in production, including backfills, reprocessing, and incident response
• Ability to turn data requirements from stakeholders into actionable plans
• Experience collaborating cross-functionally and being accountable in a small team
• Comfortable using AI-assisted tooling to accelerate development, paired with strong habits around validation, testing, and documentation
• Familiarity with product/event analytics data pipelines (Segment → warehouse) and modeling event schemas for analysis
• Experience working in a multi-cloud environment (AWS + Azure)
• Experience with orchestration and operational tooling (scheduling, retries, SLAs)
• JavaScript/TypeScript familiarity (various customer-facing aspects of our products)
• Comfort participating in production support rotations or incident response when needed