At a Glance
- Tasks: Join our Graduate Programme as a Data Engineer and work on exciting data projects.
- Company: Progeny, a forward-thinking firm revolutionising financial services with tech.
- Benefits: 30 days holiday, private medical insurance, and opportunities for personal growth.
- Other info: Collaborate with experienced professionals and gain hands-on experience with modern data platforms.
- Why this job: Kick-start your career in data engineering and make a real impact from day one.
- Qualifications: Recent technical degree and a passion for data and problem-solving.
The predicted salary is between 28800 - 48000 £ per year.
We’re excited to announce the launch of our brand-new Graduate Programme — a pilot initiative designed to bring fresh perspectives, new talent, and bold ideas into our business. This is a fantastic opportunity for a driven graduate to join us at a pivotal moment, help shape the future of the programme, and make a real impact from day one.
About the Role
We are looking for a Graduate Data Engineer who is passionate about data, problem-solving, and learning how modern data platforms are built and maintained in Azure. This role is ideal for someone who has recently completed a technical degree and wants to develop skills across data engineering, analytics engineering, and the Microsoft data ecosystem.
You will work with experienced data engineers, analysts, and architects to design, develop, and deliver high-quality data pipelines, models, and structures that support analytics, reporting, and operational data needs. The role offers hands-on experience across Azure Synapse Analytics, Azure Data Factory, Databricks, SQL, Python, and Power BI modelling, with a strong focus on modern data engineering best practices, governance, and automation. Initial projects will include building and maintaining data pipelines, supporting ingestion and transformation workflows, managing data models, and delivering structured, well-governed data to analytics teams. This role will be based at either our Leeds or Edinburgh office.
Key Responsibilities Include:
- Core Data Engineering
- Applying data engineering fundamentals, including ingestion, transformation, modelling, quality checks, and optimisation.
- Working with SQL and Python to build, maintain, and improve data processes.
- Supporting the development and maintenance of data models, both operational and analytical.
- Building, orchestrating, and monitoring data pipelines across the Microsoft data stack.
- Supporting ingestion and transformation workflows to deliver clean, reliable, structured data to analytics teams.
- Azure Data Platform
- Using Azure Synapse Analytics to manage data warehousing, compute, and analytical workloads.
- Working with Azure Data Factory (ADF) to build automated ingestion and transformation pipelines.
- Supporting development in Azure Databricks for scalable processing, notebooks, and advanced data transformations.
- Assisting with data governance and metadata management, ensuring consistency, lineage awareness, and proper stewardship.
- Analytics & Reporting Support
- Assisting with Power BI data modelling, dataset preparation, and semantic layer design.
- Ensuring that data delivered to reporting teams is structured, governed, and optimised for performance.
- DevOps & Automation
- Supporting CI/CD for data workloads using Azure DevOps or GitHub Actions.
- Contributing to automated deployment, testing, and version control of data pipelines, notebooks, and models.
- Helping to apply modern engineering practices such as code reviews, documentation, and automated checks.
- Collaboration & Knowledge Sharing
- Working closely with data analysts and business teams to understand requirements.
- Contributing to documentation for data processes, data models, lineage, and platform standards.
- Participating in knowledge sharing, stand-ups, and improvements to engineering practices.
What Success Looks Like
- Demonstrated growth in data engineering skills, including pipeline development, modelling, and data quality.
- Increasing confidence working across Azure Synapse, Data Factory, Databricks, SQL, and Python.
- Delivery of well-structured, reliable, and well-governed data assets for analytics use cases.
- Visible contribution to data platform improvements, automation, and engineering standards.
- Positive collaboration with team members and stakeholders.
Our Ideal Person
- Strong technical degree (e.g., Computer Science, Software Engineering, Data Science, Mathematics, Engineering, or similar).
- Solid grounding in programming fundamentals (ideally Python or similar high-level language).
- Sound understanding of data concepts: relational databases, SQL, data modelling, and basic analytics.
- Exposure to cloud concepts (Azure preferred) with an appetite to train into Azure Synapse and modern data platforms.
- Analytical mindset with the ability to reason about data quality, performance, and scalability.
- Comfortable learning new tools and technologies (e.g., Power BI, Azure services) in a structured environment.
- Clear communicator, curious by nature, and able to work collaboratively in cross-functional teams.
Learning/Development Opportunities
- Structured training and mentoring from experienced colleagues.
- Opportunities to contribute to real-world software projects with increasing ownership.
- Hands-on exposure to the full Microsoft data stack: Synapse, Data Factory, Databricks, Power BI, and Azure DevOps.
- Opportunities to work end-to-end on data solutions, from ingestion to modelling and deployment.
- Exposure to modern tools, technologies and frameworks.
Benefits
- 30 days' holiday plus public holidays
- 3 days of celebratory leave (to be used for your birthday, wellbeing, volunteering, or other celebratory events important to you).
- Private medical insurance, 24/7 digital GP, and health advice
- Employee assistance programme providing support for your mental and physical health
- Group pension scheme
- Life assurance scheme
- Eyecare vouchers
- Enhanced family leave
- Referral scheme
We may close this vacancy early if we receive sufficient applications. Therefore, if you are interested, please submit your application as early as possible. Please note we are aiming to hire as soon as possible and therefore if you have not yet graduated we may not be able accommodate a later start date. We will discuss this further at the application stage.
About Progeny
We create, enhance, and preserve wealth. We are the first and only firm in the UK to bring together independent financial planning, asset management, tax, HR, and private and corporate legal services.
We are forward-thinking and tech-driven, using technology to eliminate paperwork, improve communications, and enrich the relationship between client and adviser.
At Progeny, we believe that we all have the power to make good things happen. We want to use our success as a catalyst for making real change.
We are the proud winners of the Yorkshire Financial Awards 2024 Best Employer award for the third year running.
Graduate Data Engineer in Leeds employer: TargetJobs UK
Progeny is an exceptional employer, offering a unique Graduate Programme that empowers new talent to make a significant impact from day one. With a strong focus on professional development, employees benefit from structured training, hands-on experience with cutting-edge technologies, and a supportive work culture that prioritises mental and physical well-being. Located in vibrant Leeds or Edinburgh, Progeny not only provides competitive benefits but also fosters a collaborative environment where innovation thrives and personal growth is encouraged.
StudySmarter Expert Advice🤫
We think this is how you could land Graduate Data Engineer in Leeds
✨Tip Number 1
Network like a pro! Reach out to alumni from your university or connections in the industry. A friendly chat can lead to insider info about job openings and even referrals.
✨Tip Number 2
Get your hands dirty with projects! Build a portfolio showcasing your skills in SQL, Python, and Azure. This not only demonstrates your abilities but also gives you something tangible to discuss in interviews.
✨Tip Number 3
Prepare for interviews by practising common data engineering questions. Use mock interviews with friends or mentors to boost your confidence and refine your answers.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets noticed. Plus, it shows you’re genuinely interested in joining our team at Progeny.
We think you need these skills to ace Graduate Data Engineer in Leeds
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that align with the Graduate Data Engineer role. Highlight any relevant projects or coursework that showcase your data engineering knowledge and technical abilities.
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to express your passion for data and problem-solving. Share why you're excited about this opportunity at StudySmarter and how you can contribute to our team.
Showcase Your Technical Skills:Don’t forget to mention your experience with SQL, Python, and any exposure to Azure services. If you've worked on any data projects, be sure to include those details to demonstrate your hands-on experience.
Apply Early Through Our Website:We encourage you to submit your application as soon as possible through our website. The sooner you apply, the better your chances of being considered for this exciting opportunity!
How to prepare for a job interview at TargetJobs UK
✨Know Your Data Stuff
Brush up on your data engineering fundamentals, especially around SQL and Python. Be ready to discuss how you've applied these skills in your studies or projects, as this will show your passion for the role and your understanding of the technical requirements.
✨Familiarise Yourself with Azure
Since the role heavily involves Azure services like Synapse Analytics and Data Factory, take some time to explore these platforms. Mention any relevant experience or coursework during the interview to demonstrate your eagerness to learn and adapt to their tech stack.
✨Show Your Problem-Solving Skills
Prepare to discuss specific examples where you've tackled data-related challenges. Whether it's a project from university or a personal endeavour, showcasing your analytical mindset and ability to reason about data quality will resonate well with the interviewers.
✨Be Ready to Collaborate
This role emphasises teamwork, so think of instances where you've worked in groups. Highlight your communication skills and how you contributed to achieving common goals, as this will align with their focus on collaboration and knowledge sharing.
