At a Glance
- Tasks: Build scalable data pipelines and optimise storage solutions on GCP.
- Company: Join Ipsos, a leading global research company with a collaborative culture.
- Benefits: Enjoy 25 days leave, pension contributions, and flexible working options.
- Other info: Hybrid work model with opportunities for professional development and a diverse workplace.
- Why this job: Work with cutting-edge cloud technologies and make a real impact in data engineering.
- Qualifications: Experience in data engineering, strong Python skills, and cloud expertise.
The predicted salary is between 60000 - 80000 £ per year.
Ipsos is recruiting a Data Engineer to help drive the technical evolution of our Audience Measurement data platforms. Joining a wider group of engineering leaders, you will work as part of a team championing an architecture rooted in managed cloud services, cost-conscious design, and incremental improvement. You will work closely with internal teams to develop robust scalable data pipelines and optimise data storage solutions on GCP.
This is a fantastic opportunity for a mid-career / level person to work on technologies chosen intentionally, favouring proven tools that reduce cognitive load and maximise team velocity. Our core ecosystem revolves around:
- Modern Python for backend services and data processing.
- Cloud-native serverless compute and managed workflow orchestrators.
- Deep expertise in either AWS or GCP, with opportunities to cross-train on the other.
- Serverless NoSQL, Object Storage, and Serverless Analytics for our data layers.
- Event buses and messaging queues for asynchronous, decoupled processing.
- Infrastructure as Code (Pulumi/Terraform) and containerized deployments.
The role involves guiding the platform's evolution toward serverless, event-driven patterns, moving away from container-orchestrated workflows toward managed cloud services.
Platform Operations:
- Develop robust scalable data pipelines and optimise data storage solutions on GCP.
- Implement ETL processes and CI/CD pipelines to ensure clean, structured data ready for use.
- Work with data scientists to integrate synthetic models into production environments and provide the guardrails and advice as they develop.
- Provide technical support, troubleshoot issues, and research new technologies to enhance capabilities.
- Document pipelines and the platform including architectures and user guides, helping to enforce data management standards.
- Engage in DataOps practices and improve data delivery performance.
Data Science & Analytics Enablement:
- Partner with data scientists on model productionisation.
- Establish clear data contracts and shared standards that enable effective collaboration.
Agile Delivery:
- Work within an agile framework.
- Participate in agile ceremonies and provide occasional client interaction.
Team Working / Stakeholder Engagement:
- Provide technical advice and guidance for internal teams and occasionally clients.
- Explain complex technical solutions to non-technical audiences.
Continuous Improvement:
- Foster a culture of incremental improvement.
Vision and Strategy:
- Support the architectural vision as set out by the Lead Data Engineer.
About you:
To be successful in this role, your technical skills should be matched by a pragmatic approach.
- Extensive Data Engineering Experience: A proven track record of building robust scalable data pipelines using modern cloud providers (Ideally GCP).
- Strong Programming Skills: Expert-level proficiency in Python, with a strong focus on building decoupled, testable functions and clear data contracts.
- Serverless & Event-Driven Expertise: Experience with, or strong interest in, decomposing workloads into independent steps orchestrated by managed workflow services and triggered by data events.
- Migration & Testing Experience: Experience with safely modernizing legacy systems using parity testing and incremental routing patterns.
- IaC & Containerization: Hands-on experience packaging runtimes into portable containers and provisioning cloud resources using modern Infrastructure as Code tools.
- Team working / Collaboration: Experience of working with wider teams of Product Managers, Data Scientists, Engineers and non-technical staff.
We offer a comprehensive benefits package designed to support you as an individual. Our standard benefits include 25 days annual leave, pension contribution, income protection and life assurance. In addition, there are a range of health & wellbeing, financial benefits and professional development opportunities. We realise you may have commitments outside of work and will consider flexible working applications - please highlight what you are looking for when you make your application. We have a hybrid approach to work and ask people to be in the office or with clients for 3 days per week.
We are committed to equality, treating people fairly, promoting a positive and inclusive working environment and ensuring we have diversity of people and views. We recognise that this is important for our business success - a more diverse workforce will enable us to better reflect and understand the world we research and ultimately deliver better research and insight to our clients. We are proud to be a member of the Disability Confident scheme, certified as Level 2 Disability Confident Employer. We are dedicated to providing an inclusive and accessible recruitment process.
About Us: Ipsos is one of the world’s largest research companies and currently the only one primarily managed by researchers, ranking as a #1 full-service research organization for four consecutive years. With over 75 different data-driven solutions, and presence in 90 markets, Ipsos brings together research, implementation, methodological, and subject-matter experts from around the world, combining thematic and technical experts to deliver top-quality research and insights. Simply speaking, we help the biggest companies solve some of their biggest problems, serving more than 5000 clients across the globe by providing research, data, and insights on their target markets. And we are proud of our continuous efforts in making Ipsos the best place to work!
Contact Details:
Marketing Management Analytics, Inc. Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer - Audience Measurement in London
✨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 Marketing Management Analytics, Inc.!
✨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 Engineer - Audience Measurement at Marketing Management Analytics, Inc..
✨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 Marketing Management Analytics, Inc..
✨Apply Directly through Our Website
When you find a suitable opening like Data Engineer - Audience Measurement at Marketing Management Analytics, Inc., 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 Engineer - Audience Measurement in London
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 Marketing Management Analytics, Inc., 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 Marketing Management Analytics, Inc.. 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 Marketing Management Analytics, Inc.
✨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 Marketing Management Analytics, Inc.!
✨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.