At a Glance
- Tasks: Lead and enhance our data platform, ensuring top-notch data integrity and scalability.
- Company: Join a high-profile agency with a dynamic EMEA Data and Technology team.
- Benefits: Competitive salary, career growth, and the chance to shape strategic initiatives.
- Other info: Collaborative environment focused on best practices and continuous learning.
- Why this job: Make a real impact on global clients by optimising data delivery across 26+ ad platforms.
- Qualifications: Strong dbt and Python experience, with a knack for data modelling and cloud infrastructure.
The predicted salary is between 63000 - 77000 £ per year.
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 Big Query 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 Big Query
- Develop and maintain dbt macros, Jinja templates, and platform YAML definitions that auto-generate models across 26+ ad platforms
- Manage and improve GCP infrastructure (Big Query, 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 Data Ops, 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 (Power BI, 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 (Mk Docs, 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 Big Query dialect.
- Experience with Google Cloud Platform especially Big Query, 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 (Git Hub, 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, Tik Tok, 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 (Mk Docs 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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Senior Data Engineering Manager employer: Omnicom Media
Omnicom Media is an exceptional employer, offering a vibrant work culture in Greater London that prioritises collaboration and innovation. Employees benefit from continuous professional development opportunities and the chance to work with leading global brands in the automotive sector, ensuring a rewarding and impactful career path. Join us to be part of a forward-thinking team that values performance and creativity in the ever-evolving landscape of digital media.
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We think you need these skills to ace Senior Data Engineering Manager
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