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For Companies At a Glance
- Tasks: Build and maintain Python libraries for data products, enhancing performance and scalability.
- Company: Join Oxford Data Plan, a rapidly growing data science consultancy valued at £45M.
- Benefits: Enjoy a fully remote role with a competitive salary, bonus options, and sponsorship available.
- Why this job: Be part of a dynamic team shaping the future of data tools for major clients like Google and Meta.
- Qualifications: 2+ years in data or engineering, strong Python and SQL skills, and familiarity with AWS.
- Other info: Collaborate with a talented 10-person team focused on innovation and product development.
The predicted salary is between 45000 - 65000 £ per year.
Location: Fully Remote (UK-based)
Salary: £45,000–£65,000 + 10% Bonus (Cash or Equity Options)
Sponsorship: Available (preference for PSW)
About Us
We’re Oxford Data Plan, a fast-growing data science consultancy that has tripled in size since launching three years ago. Backed by $7.5M in Series A funding, we’re now valued at $45M and are powering decision-making for over 150 clients—including household names like Just Eat, Deliveroo, and even Google and Meta. Our KPI tracking tools help investment firms identify when and where to invest based on predictive analytics and performance signals.
The Role
We’re looking for a Data Systems Engineer to join our data science team. You’ll be key to building and maintaining the Python libraries that power our core data products—enhancing performance, scalability, and engineering rigour. This is a great opportunity for someone with a data science background who wants to lean more into engineering.
Your Day-to-Day
- Design, test, and maintain Python libraries that support data scalability and robustness
- Build and enhance engineering systems (unit testing, CI/CD readiness, etc.)
- Collaborate daily with data scientists and engineers on the R&D and product teams
- Help the product team develop trackers and scalable data pipelines
- Work on tools for web scraping and evaluation, ensuring data integrity and usability
What We’re Looking For
- 2+ years of hands-on experience in data or engineering roles
- Strong Python and SQL skills
- Experience working with or alongside data scientists
- Familiarity with AWS and cloud infrastructure
- Exposure to DevOps, Docker, and general engineering best practices (desirable)
- An engineering mindset with a passion for clean, scalable code
The Team
You’ll be joining a 10-person data science team that works at the intersection of product development and R&D. It’s a collaborative, cross-functional group building the next generation of data tools.
Interview Process
- Technical Interview – Live Python + SQL coding with our Data Science Manager
- Deep Dive – Technical chat with Billy (CTO) to explore problem-solving and systems thinking
Data Systems Engineer employer: Harnham
Contact Detail:
Harnham Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Systems Engineer
✨Tip Number 1
Familiarise yourself with the specific technologies mentioned in the job description, such as Python, SQL, and AWS. Being able to discuss your experience with these tools during the interview will show that you're a strong fit for the role.
✨Tip Number 2
Prepare to demonstrate your problem-solving skills through practical coding exercises. Since the interview includes live coding, practice common Python and SQL problems to build your confidence and showcase your technical abilities.
✨Tip Number 3
Research Oxford Data Plan and their clients to understand their business model and the types of projects they work on. This knowledge will help you tailor your responses and show genuine interest in how you can contribute to their success.
✨Tip Number 4
Highlight any collaborative projects you've worked on, especially those involving data science and engineering. Emphasising your teamwork skills will resonate well with the company's focus on collaboration within their data science team.
We think you need these skills to ace Data Systems Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data engineering and Python development. Emphasise any projects or roles where you've built or maintained data systems, as this aligns closely with the job description.
Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for the role and the company. Mention specific experiences that demonstrate your skills in Python, SQL, and collaboration with data scientists, as these are key aspects of the position.
Showcase Your Technical Skills: If you have experience with AWS, Docker, or DevOps practices, be sure to include this in your application. Providing examples of how you've used these technologies in past roles can set you apart from other candidates.
Prepare for Technical Interviews: Brush up on your Python and SQL skills, as you'll need to demonstrate these in the technical interview. Consider practicing coding challenges and reviewing common data engineering problems to ensure you're ready to impress.
How to prepare for a job interview at Harnham
✨Brush Up on Python and SQL
Since the role requires strong Python and SQL skills, make sure to review key concepts and practice coding problems. Be prepared to demonstrate your coding abilities during the technical interview.
✨Understand Data Systems Engineering
Familiarise yourself with the principles of data systems engineering, including scalability and robustness. Be ready to discuss how you can apply these principles in your work and provide examples from your past experience.
✨Show Your Collaborative Spirit
As you'll be working closely with data scientists and engineers, highlight your teamwork skills. Prepare examples of how you've successfully collaborated on projects in the past, especially in cross-functional teams.
✨Prepare for Technical Deep Dives
Expect a deep dive with the CTO, Billy Wildly. Think about complex problems you've solved and be ready to discuss your thought process. This is your chance to showcase your problem-solving skills and engineering mindset.
