Senior Data Engineering Manager

Omnicom Media

Greater London

On-site

GBP 90,000 - 130,000

Full time

14 days+

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Job summary

Omnicom Media is seeking an experienced Data Engineer to own and extend our config-driven data platform (DMI) within the EMEA, Data and Technology team in the UK. You will build and maintain ELT pipelines from Cloud Function ingestion into BigQuery through to dbt-powered transformations, ensuring data integrity and scalability for multiple global clients.

You will collaborate with analysts, data scientists, and BI teams to maximise value from data, mentor engineers, and drive best practices

Qualifications

  • Strong dbt experience including macros, Jinja templating, incremental models, seeds and testing.
  • 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, Pub/Sub and Cloud Scheduler.
  • Experience with Infrastructure as Code (Terraform).
  • Solid understanding of data modelling techniques (star schema, dim/fact, slowly changing dimensions).
  • Comfortable with Git, branching strategies, PRs, and CI/CD pipelines.

Responsibilities

  • Own and extend the end-to-end data pipeline from ingestion to analysis-ready tables in BigQuery.
  • Develop and maintain dbt macros, Jinja templates, and platform definitions across 26+ ad platforms.
  • Manage and improve GCP infrastructure provisioned via Terraform.
  • Build and maintain Python CLI tooling for onboarding, config compilation, and pipeline execution.
  • Mentor data engineers and promote DataOps, code reviews, testing, and documentation.
  • Identify opportunities to automate processes and redesign infrastructure for scalability.
  • Collaborate with analysts, data scientists, and BI teams to maximise data value.

Skills

dbt
Python CLI
BigQuery SQL
Google Cloud
Terraform
Data modelling
Git & CI/CD
Business requirements

Tools

Docker
CLI frameworks
MkDocs
Databricks
Pydantic

Job description

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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