At a Glance
- Tasks: Join our team to build and maintain data pipelines for global clients across 26+ ad platforms.
- Company: Be part of a high-profile agency within the Omnicom Media Data and Technology team.
- Benefits: Exciting career opportunities, collaborative environment, and the chance to shape strategic initiatives.
- Other info: Ideal for those eager to learn and grow in a dynamic, innovative setting.
- Why this job: Make a real impact in data engineering while working with cutting-edge technologies.
- Qualifications: Experience with dbt, Python, SQL, and cloud platforms like GCP is essential.
The predicted salary is between 70000 - 85000 £ per year.
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 Big Query 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 Big Query.
- 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 (Big Query, 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 (Mk Docs).
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 - Big Query, 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, Tik Tok, 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.
- #J-18808-Ljbffr
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.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineering Manager
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Omnicom Media!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Data Engineering Manager at Omnicom Media.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Omnicom Media.
✨Apply Directly through Our Website
When you find a suitable opening like Data Engineering Manager at Omnicom Media, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Data Engineering Manager
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Omnicom Media, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Omnicom Media. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Omnicom Media
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Omnicom Media!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.