Builds and operates TubeBuddy’s ETL/ELT pipelines and lakehouse/warehouse models, turning raw product, event, and YouTube-derived data into trusted datasets across our S3 data lake, Databricks, and dbt. Comfortable using AI-enhanced engineering tools in practical and reliable ways to accelerate development while maintaining correctness.
Who WE Are
TubeBuddy is a leading browser extension and platform that has helped more than 10 million YouTube creators on their YouTube journeys. Our technology is designed to help creators grow faster, through powerful search engine optimization, workflow, analytics, and productivity tools which improve per-video views and subscriber growth. TubeBuddy also serves major media companies, and global publishers. Our team is small, mighty, and deeply connected to the creator community we serve.
Excitingly, TubeBuddy was recently acquired by GameSquare on February, 20, 2026. Read the press release here:
The acquisition adds a scaled creator technology layer to GameSquare's technology platform which the Company believes will accelerate its strategy to build an integrated ecosystem spanning content, community, data, and performance marketing.
About GameSquare
GameSquare (NASDAQ: GAME) is a cutting-edge media, entertainment, and technology company transforming how brands and publishers connect with Gen Z, Gen Alpha, and Millennial audiences. With a platform that spans award-winning creative services, advanced analytics, and FaZe Clan Esports, one of the most iconic gaming organizations, we operate one of the largest gaming media networks in North America. As a digital-native business, GameSquare provides brands with unparalleled access to world-class creators and talent, delivering authentic connections across gaming, esports, and youth culture. Complementing our operating strategy, GameSquare has developed an innovative treasury management program designed to generate yield and enhance capital efficiency, reinforcing our commitment to building a dynamic, high-performing media company at the intersection of culture, technology, and next-generation financial innovation.
Who YOU Are
You are an empowered, hands-on data engineer who is comfortable owning pipelines in production. You care about data quality and correctness and you know how to keep systems stable even when inputs are messy (API constraints, schema drift, upstream failures etc…).
You are comfortable using AI-enhanced engineering tools (for example: AI-assisted SQL, code generation, and incident triage) in savvy and reliable ways, and you are excited to work at the leading edge of AI-enabled data engineering with strong validation and testing habits.
You communicate clearly and thrive working with cross-functional partners to turn product requests into well-defined outputs.
You are excited to work in a small, fluid team. While this role is primarily as a responsible for our Data Engineering systems, there will be opportunities to grow into adjacent areas like application development, backend development, and production support, depending on team needs and interests.
Responsibilities
ETL/ELT Pipelines (Batch)
- 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.
Data Modeling, dbt, and Data Quality
- 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.
Cross-Functional Support
- 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.
Qualifications
Required
- 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
Nice-to-Have
- 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.
Benefits
- Full-time remote position with salary, health, vision, dental benefits
- Flexible time-off policy
- Assistance in professional development conferences or courses
- Paid airfare, lodging if required to travel
- Other perks TBA