At a Glance
- Tasks: Design and optimise data pipelines using dbt, Python, and SQL for impactful analytics.
- Company: Join Fospha, a leading global venture builder in online retail measurement.
- Benefits: Flexible benefits, 25 days holiday plus your birthday off, and professional development opportunities.
- Other info: Dynamic work culture focused on inclusion, growth, and collaboration.
- Why this job: Make a real impact on data infrastructure and empower teams with smarter insights.
- Qualifications: Experience in data pipelines, data modelling, and familiarity with cloud-native stacks.
The predicted salary is between 63000 - 77000 £ per year.
Fospha is dedicated to building the world's most powerful measurement solution for online retail. For over a decade, we've helped teams make smarter decisions with full-funnel marketing insights, forecasting, and optimisation. With Fospha, every team moves faster and grows smarter. Trusted by over 200 leading brands across three continents, including Huel, Oh Polly, and Represent, Fospha manages $2.5 billion in annual ad spend. We're scaling fast across London, Mumbai, and Austin – and we're now looking for a Core Data Engineer to join our Core Data Team to support the growth of the business through robust, scalable data infrastructure.
The Role
As a Core Data Engineer at Fospha, you’ll be at the heart of our data ecosystem. You’ll design, build, and optimise pipelines that move, transform, and scale data across multiple systems. Working at the intersection of analytics, engineering, and machine learning, you’ll ensure our data infrastructure grows as fast as our ambitions. You’ll define data quality standards, shape the data roadmap, and support high-quality data access for our Data Science and Analytics teams. This is a high-impact role where your work will directly empower teams to move faster and deliver smarter insights.
Key Responsibilities
- Design, build, and optimise data pipelines using dbt, Python, and SQL
- Implement and maintain scalable ELT/ETL frameworks that power analytics and ML systems
- Collaborate with Data Science and Platform teams to ensure robust and reliable model deployment pipelines
- Own the reliability, scalability, and observability of data workflows in production
- Contribute to data architecture decisions and documentation, ensuring data integrity and consistency across sources
- Design and maintain data models used by ML Engineers, Data Analysts, and Data Scientists
- Drive automation, versioning, and quality validation in data delivery
- Conduct exploratory data analysis to uncover trends and inform strategic decision-making
- Identify opportunities for process improvement and promote a culture of continuous data excellence
In addition to your core responsibilities, we expect you to be excited by the opportunity GenAI brings and find new ways of working utilising our GenAI hub!
What are we looking for?
We hire for potential – you should apply if you:
- Have proven experience building data pipelines in dbt, Python, and SQL
- Demonstrate a strong grasp of data modelling, warehousing, and orchestration tools
- Understand data architecture and ELT flows
- Are familiar with ML Ops principles and how they integrate with engineering systems
- Have experience with cloud-native data stacks (preferably AWS)
- Take a pragmatic approach to balancing perfection with delivery
- Understand agile methodologies and best practices
- Know how to apply data quality frameworks and version control in data delivery
Our Values and Principles
You will be able to demonstrate examples of our core principles:
- Seek inclusion & diversity: We create an environment where everyone feels welcome, and people are encouraged to speak and be heard
- Work Hard, Work Well, Work Together: We take responsibility for making things happen, independently and together; we help colleagues in need and close loops, making sure our work is complete and has lasting impact
- Grow: We are proactive, curious and unafraid of failure
- Customer at the heart: We care about the customer, feel their pain and love building product that solves their biggest problems
- Candour with caring: We deliver candid feedback with kindness and receive it with gratitude
What we can offer you
- Be part of a leading global venture builder, and learn from the incredible talent in BC
- Be exposed to the right mix of challenges and learning and development opportunities
- Flexible Benefits including Private Medical and Dental, Gym Subsidiaries, Life Assurance, Pension scheme etc
- 25 days of paid holiday + your birthday off!
Data Engineer employer: The BDPN
At Zynga, we pride ourselves on fostering a vibrant and inclusive work culture that thrives on creativity and collaboration. As a Senior UI/UX Designer at Gram Games, you'll enjoy exceptional benefits including a competitive salary, private medical care, and a company bonus scheme, all while working in a dynamic environment filled with innovative technology and delicious onsite meals. Join us in the UK and take advantage of unparalleled growth opportunities in the gaming industry, where your contributions will directly impact the joy of players worldwide.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer
✨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 The BDPN!
✨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 at The BDPN.
✨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 The BDPN.
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We think you need these skills to ace Data Engineer
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 The BDPN, 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 The BDPN. 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 The BDPN
✨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 The BDPN!
✨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.
