About the Role
We're looking for a Lead Data Engineer to join the Paid Media Insights team within Better Collective. Paid media is where the data has to pay off. We spend real money across dozens of ad networks every day. Which campaigns scale, which creatives get cut and which markets get budget comes out of this team's models.
Responsibilities
•Every data job in paid media. All of it. Freshness, cost, reliability, alerting, and the 07:30 incident before the spend review.
•The end-to-end user-level model. Ad platform spend and delivery, affiliate and operator revenue and CRM, joined into one view the business trusts enough to move budget on.
•Ingestion of paid media sources on the platform's framework: which sources, which schemas, and what happens when a network changes its API unannounced.
•The domain's models, from staging to the marts analysts query, plus the semantic meaning on top.
•Reverse ETL into the ad platforms, so conversion data lands where it changes bidding.
•The handover, taking over the paid media jobs the central team still runs for us.
•Technical lead for the data engineers in Paid Media Insights: setting the standard for how this domain builds, reviewing, unblocking, and growing them by giving away the interesting problems.
•Shaping the domain's roadmap with the Senior Head of Paid Media Insights, the analysts and the business teams.
•Representing paid media in platform conversations, including how we support machine learning and data science.
•Hands-on technical leadership, not a step away from building. You will be in the code.
Requirements
•You take ownership, and it shows up in the boring parts. You want the pager as well as the model, and would rather own a domain end to end than hand off the consequences.
•You break complex systems into simple parts. Attribution windows, late conversions, identity across platforms, dozens of disagreeing source APIs - you hold that and still hand the business something it can reason about.
•You raise the people around you. Colleagues come to you for technical advice. You review generously, give feedback that lands, and would rather the whole team understand the pipeline than be the only one who does.
•You work well with a platform team. Strong opinions about standards, still happy to work inside someone else's. You know a constraint worth fighting from a preference worth dropping.
•You are already past prompting. AI is part of how you engineer, and you have a view on what a data domain needs to be for agents to be useful on top of it: documented, standardised, semantically clear.
•You are close to the business. You will sit with the marketers and analysts spending budget on what you build, and can talk data with people who do not think in tables.
•You are technically deep where it counts. Production pipelines in SQL and Python, dbt and Dagster, cloud data warehousing, and a real feel for performance, cost and reliability at scale.
Nice to Have
•Paid media or attribution experience is a bonus.
•If you have built production pipelines on Snowflake, BigQuery or Redshift and you are curious about where we are going, that transfers.
Benefits
•Private health insurance
•Sick leave 100% paid
•Canteen with free meals and drinks
•Flexible working hours
•Additional vacation days after two years in the company
•Up-to-date equipment, entertainment facilities in a modern office right in the city center, and more
