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Role Description

This role involves building and operating 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.

• 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.

Qualifications

• 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

Requirements

• 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