Manager, Data Engineering
Summary
Data engineering manager building a config-driven platform that ingests, transforms, and delivers paid media data from 26+ ad platforms. Day to day: ELT pipelines from Cloud Functions into dbt transformations in BigQuery, Python CLI tooling, GCP infrastructure upkeep, and testing/CI with pytest and Cloud Build.
In this role, you will contribute to a config-driven data engineering platform that standardises ingestion, transformation, and delivery of paid media data across 26+ ad platforms. You will help build and maintain scalable ELT pipelines from Cloud Function ingestion to dbt-powered transformations in BigQuery, partnering with analysts and BI teams. The role offers opportunities to shape a mature data platform within a high-profile team and drive engineering best practices. You’ll work hands-on to extend platform coverage and ensure data integrity and scalability.
Responsibilities- Contribute to end-to-end data pipelines from Cloud Function ingestion to dbt transformations and analysis-ready BigQuery tables
- Develop and maintain dbt models, macros, and Jinja templates within a macro-first framework for 26+ ad platforms
- Add platform integrations using YAML definitions and Python ingestion functions
- Contribute to Python CLI tooling for client onboarding, config compilation, and pipeline execution
- Maintain GCP infrastructure (BigQuery, Cloud Run, Cloud Functions, Cloud Scheduler) with senior guidance
- Write and maintain tests (pytest, dbt tests) and support CI/CD pipelines (Cloud Build)
- Collaborate with analysts and BI teams to ensure data models meet reporting needs
- Participate in code reviews and contribute to documentation (MkDocs)
- dbt: writing models, Jinja basics, tests and seeds
- Python: scripting, Pandas, reading existing codebases
- SQL: complex queries, joins, aggregations, window functions
- Experience with at least one cloud platform (GCP preferred; AWS or Azure relevant)
- Git basics and CI/CD concepts (branching, PRs)
- Familiarity with data modelling concepts (tables, views, star schema)
- eagerness to learn
- curiosity
- attention to detail
- dbt macros, Jinja templating, incremental models, or packages
- Google Cloud Platform services - BigQuery, Cloud Functions, Cloud Storage, Cloud Run
- Docker and containerised workloads