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Better Collective

Lead Data Engineer

NewDataLeadNis, Nišavski okrug, SerbiaPaid MediaAttributionCRM

Our Take

Lead Data Engineer to own and build end-to-end paid media models on MotherDuck and dbt.

What you’ll do

  • Own every data job in paid media
  • Build the end-to-end user-level model
  • Ingest paid media sources on the platform framework
  • Lead a group of engineers in Paid Media Insights

What they’re looking for

  • Production pipelines in SQL and Python
  • dbt and Dagster experience
  • Cloud data warehousing
  • Paid media or attribution experience

What you get

  • Private health insurance
  • Sick leave 100% paid
  • Canteen with free meals and drinks

As posted by Better Collective

We’re looking for an Lead Data Engineer to join the Paid Media Insights team within Better Collective.

The Domanin

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.

  • Ad platform spend and delivery, affiliate and operator revenue and CRM, stitched into one user-level view of what a click was worth. That model exists and it works.

  • The most demanding domain on our platform: the most sources, the fastest schema churn, the shortest patience for a late table. We want the engineer who owns it.

Where this role sits

A central platform team sets the how. You set the what.

  • A central team owns the platform - MotherDuck, dbt, Dagster, DLT, the infrastructure. Paid Media Insights is a spoke in that hub and spoke organisation, building on it.

  • The split is deliberate: the platform team decides how data is produced, you decide what paid media produces and own everything we run. No new stack to build, and no year lost to plumbing a central team should solve once.

  • Be a demanding customer: when a golden path does not fit paid media, push for it to change rather than quietly building around it.

  • You report to the Senior Head of Paid Media Insights and work across Paid Media, with the Campaign, Commercial, CRM and platform teams.

What you will own

Every data job in paid media. All of it.

  • Freshness, cost, reliability, alerting, and the 07:30 incident before the spend review. A paid media model that is wrong or late is yours, not the platform team’s - that accountability is the core of the role.

  • 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. Nobody at the centre can define a qualified signup in paid media. You can.

  • 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.

What you will lead

A group of engineers, and the standard they build to

  • 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.

What we’re looking for

More than a stack match, we are looking for a particular way of working.

  • 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. Paid media or attribution experience is a bonus.

Our Stack

What you will build on

MotherDuck / DuckDB   ·   dbt   ·   Dagster   ·   DLT   ·   Python   ·   SQL   ·   AWS   ·   reverse ETL and semantic layer tooling

We do not expect you to have worked with all of these. 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

We also provide up-to date equipment, entertainment facilities in a modern office right in the city center and more.

Application Deadline

We look forward to hearing from you and accept applications until 28th November.
Please submit your CV and cover letter in PDF; only applications submitted in English will be considered.

Expected start date: as soon as possible.

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