Data Engineer

What you'll do
Build and own the ingestion pipelines for Network sources — YouTube CMS/Analytics, AVOD/FAST platforms, Google Ad Manager and Google Ads (landing directly in BigQuery), and— including the API integrations, scheduling, and monitoring behind them.
Contribute to the shared conformed dimensions (Period, Title, Platform/Counterparty, Contract, and others) rather than building source-specific silos. the point is one conformed number the business can trust across processes.
Help crack campaign-to-brand attribution for Media Solutions — connecting HubSpot campaigns and GAM targeting back to the asset/brand they drove. This is the most important open architectural problem on the Network side and a core part of the role.
Build data-quality checks, reconciliation logic, and tests into the pipeline so issues are caught in the warehouse.
What we're looking for
5+ years of data engineering experience, with a strong track record of building and operating production data pipelines.
2+ years hands-on with BigQuery and GCP, with strong, demonstrable SQL — window functions, complex joins, and cost-aware query patterns.
Write and optimize BigQuery SQL transformations, models, and analytical queries with attention to correctness, performance, and cost.
Develop pipeline code in Python — ingestion, orchestration, testing, and packaging.
Implement data models across the raw, staging, curated, and semantic layers
Implement data quality, reconciliation, and validation checks so that incomplete or incorrect data cannot silently reach reporting.
Own the reliability of your pipelines — monitoring, alerting, freshness, and incident response for the data flows you build.
Optimize BigQuery cost and performance through partitioning, clustering, and efficient query patterns.
Follow and contribute to engineering standards version control, CI/CD, testing, documentation, and lineage and uphold them in code review.
Contribute to design discussions and propose approaches, while working within the architecture and standards set by the Data Lead.
Partner with finance and business stakeholders to understand reporting needs and translate them into durable, tested data models rather than one-off extracts.
Nice to have
Media, entertainment, or streaming domain background — YouTube monetisation, AVOD/FAST economics, or ad-supported revenue models.
Familiarity with HubSpot data, marketing attribution, or campaign analytics.
Exposure to GCP beyond BigQuery (IAM, service accounts, Cloud Storage), and to identity/auth patterns like Workload Identity Federation.
Roblox or games-platform data experience.

Employment type
Full-time

Work arrangement
Hybrid