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Senior Manager, Data Engineering

Reads like a Data Leadership role: running a data team.

London, London, United Kingdom

Pay
Pay not listed
Work setting
Not stated
Employment
Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting
Apply at interpublic

What you’ll work on

Full posting
  • 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.

From the employer’s posting
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.
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.
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.

What you’ll bring

All qualifications

Core experience

  • Strong experience with dbt - macros, Jinja templating, incremental models, seeds, testing, and packages.
  • Experience with Docker and containerised workloads (Cloud Run Jobs).
  • Experience with Databricks (and dbt-databricks).
  • Ownership – an ability to manage multiple workstreams across clients with accuracy, and see things through from design to deployment.
  • Proficient in Python 3.11+ building CLI tools, data processing, and automation.
  • Familiarity with CLI frameworks (Click) and config-driven architectures (Pydantic, YAML-based configuration).
Qualification wording
Strong experience with dbt - macros, Jinja templating, incremental models, seeds, testing, and packages.
Experience with Docker and containerised workloads (Cloud Run Jobs).
Experience with Databricks (and dbt-databricks).
Ownership – an ability to manage multiple workstreams across clients with accuracy, and see things through from design to deployment.
Proficient in Python 3.11+ building CLI tools, data processing, and automation.
Familiarity with CLI frameworks (Click) and config-driven architectures (Pydantic, YAML-based configuration).

Tools in this posting

  • Python
  • SQL
  • AWS
  • Azure
  • BigQuery
  • Databricks
  • dbt
  • Docker
  • GCP
  • Looker
  • Power BI
  • S3
  • Tableau
  • Terraform
Source — Tool mentions in context
- 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.
- 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 Databricks (and dbt-databricks). - Familiarity with modern Python dev tooling — Poetry, ruff, mypy, pre-commit. - Experience with docs-as-code (MkDocs or similar).
- 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
- 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.
This role sits within our 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 beneficial.
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.
- 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.
- 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.
Nice to Have: - Experience with Databricks (and dbt-databricks). - Familiarity with modern Python dev tooling — Poetry, ruff, mypy, pre-commit.
- 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.
- Collaborate with analysts, data scientists, and BI teams (PowerBI, Looker Studio, Tableau, etc.) to maximise the value delivered from data models. - 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.
Highly Desirable: - Experience with Docker and containerised workloads (Cloud Run Jobs). - Familiarity with CLI frameworks (Click) and config-driven architectures (Pydantic, YAML-based configuration).
- 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 models. - Contribute to CI/CD pipelines (Cloud Build), testing (pytest, dbt tests), and documentation (MkDocs, etc.).
- 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).

Posting record

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Oct 22, 2026

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Job description

View original posting ↗

Agency:

Omnicom Media

Job Function:

Data and Analytics

Job Subfunction:

Data Engineering

Job Description:

This role sits within our 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 beneficial.

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 models.
  • 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

Omnicom Media is the media services division of Omnicom, bringing together some of the world's most recognised agency brands, specialist capabilities, and media expertise. We operate one of the industry's strongest media ecosystems, designed to help our clients unlock growth through intelligence, innovation, and collaboration.

 

Everything we build, from systems and platforms to products and capabilities, is designed with growth in mind. Our integrated Growth Ecosystems are tailored to each client's ambitions: modular, intelligent, and adaptable, deploying the right capabilities at the right time to create meaningful impact and drive transformational results.

 

40,000+ people - Our scale is powered by our talent. With access to global expertise, local market insight, and operational excellence, our teams work together to deliver smarter solutions for clients around the world.

70+ markets - Our global reach enables us to create strategies informed by culture, commerce, and consumer behaviour, ensuring relevance in every market.

150+ cities - With teams embedded in communities worldwide, we combine local knowledge with global perspective to help clients navigate an ever-evolving media landscape.

 

Join Omnicom Media and be part of a global network where your ideas, expertise, and ambition can help shape the future of media.





To the extent permissible by local law, Omnicom’s policy requires employees to work in the office for a minimum of three days a week, unless additional in-office days are directed by their agency or manager.


Omnicom is committed to hiring and developing exceptional talent. We agree that talent is uniquely distributed, and we’re focused on developing inclusive teams that can bring the best solutions to everything we do. We strongly believe that celebrating what makes us different makes us better together. Join us—we look forward to getting to know you. We will process your personal data in accordance with our Recruitment Privacy Notice.


Link to Recruitment Privacy Notice: https://www.omc.com/privacy-notice/

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