Senior Data Engineering Manager

This role sits within our EMEA, Data and Technology team.

In this role, you will own and extend our config-driven data platform (DMI), which standardises ingestion, transformation, and delivery of paid media data across 26+ ad platforms for multiple global clients. You will work closely with our team to build and maintain ELT pipelines from Cloud Function ingestion into BigQuery through to dbt-powered transformation ensuring the highest standard in data integrity and scalability.

This is an exciting role with excellent career opportunities within a high-profile team and scope to strategically shape the agency. We are looking for someone who can hit the ground running, contribute to a mature mono-repo data platform, and help drive best practices across the engineering team. Experience with digital media data is highly beneficia

Responsibilities

• Own and extend the end-to-end data pipeline from Cloud Function ingestion through dbt transformation (staging → intermediate → marts) to analysis-ready tables in BigQuery
• Develop and maintain dbt macros, Jinja templates, and platform YAML definitions that auto-generate models across 26+ ad platforms
• Manage and improve GCP infrastructure (BigQuery, Cloud Run, Cloud Functions, Cloud Scheduler, Pub/Sub) provisioned via Terraform.
• Build and maintain the Python CLI tooling that orchestrates client onboarding, config compilation, and pipeline execution
• Mentor the team of data engineers, driving best practices in DataOps, code review, testing, and documentation.
• Proactively review existing processes to identify opportunities to automate manual work, optimise data delivery, and re-design infrastructure for greater scalability
• Collaborate with analysts, data scientists, and BI teams (PowerBI, Looker Studio, Tableau, etc.) to maximise the value delivered from data mode IS.
• Contribute to CI/CD pipelines (Cloud Build), testing (pytest, dbt tests), and documentation (MkDocs, etc).

About You

Required:

• Strong experience with dbt - macros, Jinja templating, incremental models, seeds, testing, and packages.
• Proficient in Python 3.11+ building CLI tools, data processing, and automation.
• Proficient in SQL, ideally BigQuery dialect.
• Experience with Google Cloud Platform especially BigQuery, Cloud Run, Cloud Functions, Cloud Storage, Pub/Sub, and Cloud Scheduler
• Experience with Infrastructure as Code (Terraform) for provisioning and managing cloud resources.
• Solid understanding of data modelling techniques (star schema, dim/fact architecture, slowly changing dimensions)
• Comfortable with Git (GitHub, branching strategies, pull requests) and CI/CD (Cloud Build or similar)
• Ability to translate business needs into technical specifications.

Highly Desirable:

• :Experience with Docker and containerised workloads (Cloud Run Jobs.)
• Familiarity with CLI frameworks (Click) and config-driven architectures (Pydantic, YAML-based configuration)
• Knowledge of the digital media / paid media industry — we process data from 26+ ad platforms (Google Ads, Meta, DV360, TikTok, etc)
• Exposure to multi-cloud integrations (Azure Blob, AWS S3, SFTP)
• Mono-repo experience — managing multi-client configurations in a single codebase.

Nice to Have

Experience with Databricks (and dbt-databricks.)

• Familiarity with modern Python dev tooling — Poetry, ruff, mypy, pre-commit.
• Experience with docs-as-code (MkDocs or similar).

Qualities:

• Ownership – an ability to manage multiple workstreams across clients with accuracy, and see things through from design to deployment.
• Curiosity – a natural inclination to explore new tools, dig into unfamiliar systems, and understand how things work end-to-end.
• Resourcefulness – an ability to unblock yourself, whether that means reading source code, querying logs, or finding creative workarounds when data or documentation is limited.
• Problem-solving – an ability to think through complex data issues methodically and design clean, maintainable solutions.
• Collaboration – a desire to work openly, share knowledge, and build a team culture where code reviews and pair programming are valued.

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