Data Engineering Manager

Omnicom Media; Greater London; On-site; GBP 65,000 - 95,000; Full time

Job summary

Omnicom Media in London is seeking a data engineer to join the Data and Technology team to support the config-driven data platform (DMI) powering 26+ ad platforms for global clients.

You will build and maintain ELT pipelines from Cloud Function ingestion into BigQuery, with dbt-powered transformations, ensuring data quality and scalable architecture. Collaborate with analysts and BI teams to meet reporting needs and drive best practices.

Qualifications

• Experience with dbt: models, Jinja basics, tests, seeds.
• Strong Python skills, Pandas, and reading existing codebases.
• Expert SQL: joins, aggregations, window functions.

Responsibilities

• Contribute to end-to-end data pipeline from ingestion to marts in BigQuery.
• Write and update dbt models and Jinja templates in a macro-first framework.
• Add platform integrations via YAML definitions and Python ingestion functions.
• Develop Python CLI tooling for client onboarding and pipeline orchestration.
• Maintain GCP infrastructure (BigQuery, Cloud Run, Functions, Scheduler) under guidance.
• Write tests (pytest, dbt tests) and support CI/CD pipelines (Cloud Build).
• Collaborate with analysts/BI teams to ensure data models meet reporting needs.
• Participate in code reviews and contribute to MkDocs documentation.

Skills

dbt

Python

SQL

Cloud platforms

Git

CI/CD

Data modelling

Tools

BigQuery

Cloud Run

Cloud Functions

Cloud Scheduler

Docker

Terraform

Pandas

dbt

Databricks

Job description

This role sits within our Omnicom Media Data and Technology team.

In this role, you will contribute to our config-driven data engineering platform (DMI), which standardises ingestion, transformation, and delivery of paid media data across 26+ ad platforms for multiple global clients. You will work alongside other like minded data engineers to build and maintain ELT pipelines - from Cloud Function ingestion into BigQuery through to dbt-powered transformation - ensuring a high 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 beneficial.

Responsibilities

• Contribute to the end-to-end data pipeline - from Cloud Function ingestion through dbt transformation (staging → intermediate → marts) to analysis-ready tables in BigQuery.
• Write and update dbt models, macros, and Jinja templates, working within our macro-first framework that auto-generates models across 26+ ad platforms.
• Add new platform integrations and extend existing ones using platform YAML definitions and Python ingestion functions.
• Contribute to the Python CLI tooling that orchestrates client onboarding, config compilation, and pipeline execution.
• Help maintain GCP infrastructure (BigQuery, Cloud Run, Cloud Functions, Cloud Scheduler) with guidance from senior engineers.
• Write and maintain tests (pytest, dbt tests) and support CI/CD pipelines (Cloud Build).
• Collaborate with analysts and BI teams (Power BI, Looker Studio, Tableau, etc.) to ensure data models meet reporting needs.
• Participate in code reviews, suggest improvements, and contribute to documentation (MkDocs).

About You

Required

• Experience with dbt - writing models, using Jinja basics, running tests and seeds.
• Good knowledge of Python - comfortable writing scripts, working with libraries like Pandas, and reading existing codebases.
• Expert knowledge of SQL - writing queries, joins, aggregations, and window functions.
• Experience with at least one cloud platform (GCP preferred, but AWS or Azure also relevant).
• Comfortable with Git (branching, pull requests, code reviews) and basic CI/CD concepts.
• Familiarity with data modelling concepts (tables, views, star schema basics).

Highly Desirable

• Experience with Google Cloud Platform services - BigQuery, Cloud Functions, Cloud Storage, or Cloud Run.
• Experience with dbt macros, Jinja templating, incremental models, or packages.
• Familiarity with Docker and containerised workloads.
• Exposure to Infrastructure as Code (Terraform).
• Knowledge of the digital media / paid media industry - we process data from 26+ ad platforms (Google Ads, Meta, DV360, TikTok, etc.).

Nice to Have

• Familiarity with CLI frameworks (Click) or config-driven architectures (Pydantic, YAML).
• Experience with modern Python dev tooling - Poetry, ruff, pre-commit.
• Exposure to multi-cloud integrations (Azure Blob, AWS S3, SFTP).
• Experience with Databricks.

Qualities

• Eagerness to learn – a genuine interest in growing your skills across the data stack, from SQL and Python to cloud infrastructure.
• Curiosity – a natural inclination to explore new tools, ask questions, and understand how things work.
• Attention to detail – care about getting data right, writing clean code, and following established patterns.
• Problem-solving – an ability to think through data issues methodically and ask for help when needed.
• Collaboration – a desire to work openly, participate in code reviews, and learn from more experienced engineers.