Data Engineer in Banbury

Data Engineer in Banbury

Banbury Full-Time 43000 - 51000 £ / year (est.) No working from home possible
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At a Glance

  • Tasks: Design and build scalable data pipelines and influence data architecture.
  • Company: Join a global leader in financial services with a focus on innovation.
  • Benefits: Competitive salary, private healthcare, flexible benefits, and 25 days holiday.
  • Other info: Inclusive culture where your voice matters and career growth is encouraged.
  • Why this job: Shape the future of data while making a real impact on business decisions.
  • Qualifications: Experience with Databricks, Python, Spark, and Azure required.

The predicted salary is between 43000 - 51000 £ per year.

Flexible Location | Hybrid working with frequent travel to Banbury required.

Ever built a data pipeline and wondered… is anyone really using this? Ever wanted more say in the architecture, the tools, the direction and not just the tickets in the sprint? This might be your kind of role. We’re right at the start of our data journey. Not maintaining something someone else built five years ago, but designing and building a modern Databricks Lakehouse on Azure from the ground up and we need a Data Engineer who’s as curious about why we’re doing it as how we’re doing it.

The role: Because we’re at the beginning, you’ll help shape the architecture, influence standards and frameworks, work across a broad range of data challenges and see your work directly impact executive and operational decision-making across the business, both in the UK and internationally.

You’ll:

  • Design and build scalable data pipelines (ETL/ELT) pulling from core platforms, cloud storage, databases and APIs.
  • Turn raw, messy, disparate data into curated, analysis-ready datasets.
  • Work with Python, Spark and SQL every day.
  • Develop models and schemas using a medallion architecture approach.
  • Help shape our data architecture with the Data Architect.
  • Implement governance, quality checks and access controls (Unity Catalogue).
  • Optimise for performance, reliability and scalability in Azure.
  • Contribute to CI/CD and DevOps practices in Azure DevOps.

But here’s the bit that makes this different: You won’t just be “building pipelines”, you’ll be building understanding. You’ll care about what the data is telling the business and be curious about what decisions it informs. You’ll ask, “Is this the best way to do it?”, and then you’ll make it better.

What you’ll be doing: Anyone can move data from A to B, but really good looks like this:

  • Pipelines that are elegant, scalable and observable.
  • Clean, well-documented models analysts actually enjoy working with.
  • Thoughtful performance tuning.
  • Governance built in, not bolted on.
  • Constant refinement and efficiency improvements.

We’re working with a wide and interesting range of data sources from financial, operational, external and structured (and maybe not-so-structured). There’s plenty of variety and plenty of opportunity to improve things. If you get a quiet satisfaction from shaving minutes off a job runtime, refactoring something clunky into something beautiful, or discovering a better tool to solve a problem you’ll fit right in.

What you’ll bring: You’ll likely have:

  • Hands-on expertise with Databricks.
  • Confidence in Python, Spark and SQL.
  • Experience building pipelines in Azure.
  • A solid understanding of data modelling and scalable architectures.

But just as important: You’re inclusive and curious and care about doing things properly and enjoy solving problems others can’t. You like working in a small team where your voice matters. This isn’t a “sit quietly and code what you’re told” environment. You’ll have a genuine say in how we do things, how we design things, and where we’re heading next.

The good stuff: The Tech you’ll Get to Play With: Databricks, Azure (cloud-native data services), Python, Spark & SQL. This is your chance to work with modern, “shiny” tools and influence what we adopt next. Use workflow tools such as ADF / Airflow and big data technologies (Spark, Hadoop, Kafka).

Private healthcare for you and your family.

Company pension scheme.

Flexible benefits (gym membership, tech, health assessments and more).

Access to an online wellbeing centre.

Discounts with a wide range of retailers.

25 days' holiday plus bank holidays, increasing with service, with buy/sell options.

Electric Vehicle / Plug-in Hybrid Vehicle scheme.

About Bibby Financial Services: We’re a global organisation operating in nine countries, supporting over 9,000 SMEs worldwide. Following the completion of a £1bn securitisation deal, we’re increasing our lending to UK businesses at a time when support really matters and this role plays a vital part in making that happen.

If You’re Thinking… “I want to build something properly.” “I want to understand the business impact of what I’m building.” “I want to work with modern tools and have a real say.” Then let’s talk.

Apply before 31st March 2026. Early applications are encouraged, as the role may close sooner. Everyone will receive a response. Bibby Financial Services is committed to creating an inclusive workplace. If you require any adjustments during the recruitment process, please let us know.

Data Engineer in Banbury employer: Bibby Financial Services

At Bibby Financial Services, we pride ourselves on being an excellent employer that values innovation and collaboration. Our flexible working environment, combined with opportunities for personal and professional growth, allows our Data Engineers to shape the future of our data architecture while enjoying a supportive culture that encourages curiosity and inclusivity. With competitive benefits, including private healthcare and a generous holiday allowance, we ensure our employees feel valued and empowered to make a meaningful impact in their roles.

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Contact Details:

Bibby Financial Services Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Data Engineer in Banbury

Tip Number 1

Network like a pro! Reach out to people in the industry, attend meetups, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.

Tip Number 2

Show off your skills! Create a portfolio showcasing your data pipelines, models, and any cool projects you've worked on. This is your chance to demonstrate your expertise in Python, Spark, and SQL, and how you can make an impact.

Tip Number 3

Prepare for interviews by understanding the company’s data journey. Research their current data architecture and think about how you can contribute to building something amazing. Be ready to discuss your ideas and ask insightful questions!

Tip Number 4

Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are genuinely interested in joining our team and shaping the future of data together.

We think you need these skills to ace Data Engineer in Banbury

Data Pipeline Design
ETL/ELT Processes
Python
Spark
SQL
Databricks
Azure

Some tips for your application 🫡

Show Your Curiosity:When writing your application, let us see your curiosity shine through! Talk about why you’re interested in the role and how you want to contribute to our data journey. We love candidates who ask questions and want to understand the bigger picture.

Be Specific About Your Skills:Make sure to highlight your hands-on experience with Databricks, Python, Spark, and SQL. We want to know exactly how you've used these tools in your previous roles. Share specific examples of projects where you’ve built scalable data pipelines or optimised performance.

Keep It Clean and Clear:Just like we value clean data, we appreciate a well-structured application! Use clear headings, bullet points, and concise language to make it easy for us to read. A tidy application reflects your attention to detail, which is crucial for a Data Engineer.

Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates. Plus, it shows you’re keen to join our team!

How to prepare for a job interview at Bibby Financial Services

Know Your Data Tools

Make sure you brush up on your knowledge of Databricks, Python, Spark, and SQL. Be ready to discuss how you've used these tools in past projects, especially in building scalable data pipelines. Show them you’re not just familiar with the tech but that you can also articulate its impact on business decisions.

Show Your Curiosity

This role values curiosity about data and its implications. Prepare questions that demonstrate your interest in understanding the business side of data engineering. Ask about the challenges they face and how your role could help solve them. This shows you’re not just a coder; you’re a problem solver.

Highlight Your Team Spirit

Since this position involves working closely with a small team, be ready to share examples of how you’ve collaborated effectively in the past. Discuss how you value inclusivity and how you’ve contributed to a positive team environment. They want someone who can communicate and work well with others.

Prepare for Practical Scenarios

Expect to tackle practical scenarios or case studies during the interview. Brush up on your ETL/ELT processes and be prepared to discuss how you would approach designing a data pipeline from scratch. Think about performance tuning and governance as you prepare your answers.