Data Engineering Manager

Data Engineer

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.