At a Glance
- Tasks: Join our Data & Analytics team to build and maintain scalable cloud-based data solutions.
- Company: DF Capital, a specialist bank focused on innovative financial solutions.
- Benefits: Competitive salary, private medical and dental insurance, gym membership, and generous leave.
- Other info: Collaborative culture with opportunities for professional growth and community support.
- Why this job: Make a real impact in a dynamic environment while developing your data engineering skills.
- Qualifications: Strong SQL skills and experience with cloud-based data architectures required.
The predicted salary is between 63000 - 77000 £ per year.
We’re DF Capital – a specialist bank providing award-winning commercial finance, retail finance, and savings products to consumers and small businesses.
Based in Manchester, we serve thousands of customers across the UK and into Europe, supporting their ambitions with tailored financial solutions.
We help our customers realise their ambitions by doing things differently – combining the agility and innovation of a specialist lender with the security and service standards of a regulated bank.
Whether it’s flexible lending structures or straightforward savings options, we focus on what matters most to our customers.
In 2025, we launched DF Capital Retail Finance – a subsidiary of DF Capital Bank Limited – to offer specialist hire purchase solutions to retail customers.
Our goal is simple: to do the absolute best for our customers, our communities, and each other.
Your new role
We are seeking a Data Engineer to join our growing Data & Analytics team within a medium-sized UK bank.
Working in a small, agile, you will play a key role in sourcing, integrating, transforming and delivering data from a variety of internal and external systems.
You will be responsible for building and maintaining scalable cloud-based data solutions, ingesting structured data from databases and operational systems, as well as semi-structured data from APIs and third-party services.
Using Snowflake, DBT and Windmill, you will develop robust data pipelines that support regulatory reporting, operational processes, business intelligence and analytical workloads.
This role is well suited to an engineer who enjoys taking ownership, working across the full data lifecycle, and contributing to the continued development of a modern cloud data platform within a regulated financial services environment.
- Data Engineering & Development
- Design, develop and maintain scalable data pipelines and data integration solutions.
- Build and optimise SQL-based solutions within Snowflake.
- Create and maintain robust ELT processes supporting reporting and analytics requirements.
- Develop and manage data models that support business, operational and regulatory needs.
- Ensure data quality, consistency and integrity across multiple data sources.
- Document data flows, transformation logic and technical solutions.
- Data Integration & Ingestion
- Design and maintain ingestion pipelines for both structured and semi-structured data.
- Source and integrate data from operational databases, applications and third-party platforms.
- Develop integrations with REST APIs and other external data services.
- Extract, process and transform semi-structured data formats such as JSON and XML.
- Monitor ingestion processes and implement controls to ensure data reliability and completeness.
- Work with business and technical stakeholders to understand source systems and data requirements.
- Data Transformation & Modelling
- Build and maintain transformation layers using SQL and DBT.
- Design reusable and scalable data models following engineering best practices.
- Implement testing and validation to ensure high levels of data quality.
- Optimise transformation performance and maintainability.
- Platform Automation & Orchestration
- Develop and maintain automated workflows using Windmill.
- Schedule, orchestrate and monitor data processing activities.
- Identify opportunities to improve operational efficiency through automation.
- Support troubleshooting and resolution of production issues.
- Dev Ops & CI/CD
- Use Git Hub for source control, collaboration and code reviews.
- Support and improve CI/CD processes for data platform deployments.
- Promote engineering best practices including version control, testing and release management.
- Maintain technical documentation and operational runbooks.
- Collaboration & Continuous Improvement
- Work closely with the Lead Data Engineer and wider stakeholders across the bank.
- Participate in architecture discussions and solution design.
- Contribute to the evolution of the data platform and engineering standards.
- Share knowledge and support continuous improvement initiatives within the team.
Essential Skills & Experience
- Technical Skills
- Strong SQL skills with experience developing complex queries, transformations and data models.
- Experience working with modern cloud-based data architectures and data platforms.
- Experience sourcing and integrating data from structured sources such as relational databases.
- Experience working with semi-structured data including JSON, XML and API-based integrations.
- Familiarity with Python for automation, scripting, API integration and data processing.
- Experience designing and maintaining data transformation pipelines.
- Good understanding of data warehousing concepts and dimensional modelling.
- Experience working with Git-based source control and collaborative development practices.
- Understanding of CI/CD principles and automated deployment processes.
- Knowledge of data quality, testing and monitoring methodologies.
- Professional Experience
- Experience working as a Data Engineer, ETL Developer or similar role.
- Experience delivering data solutions within a cloud environment.
- Ability to work independently and manage priorities effectively.
- Strong analytical and problem-solving skills.
- Excellent communication skills with both technical and non-technical stakeholders.
Desirable Skills & Experience
- Experience with
DBT for data transformation and modelling.
- Experience with
Windmill for workflow orchestration and automation.
- Experience building internal data applications using
Streamlit .
- Experience with
Snowflake administration and optimisation.
- Knowledge of financial services, banking or regulated industries.
- Exposure to regulatory reporting and data governance frameworks.
- Experience working in Agile delivery teams.
- Technology Stack
- Core Technologies
- Snowflake
- (Data Warehouse)
- SQL
- Python
- Git Hub
- CI/CD Pipelines
- Data Engineering & Automation
- DBT
- Windmill
- REST APIs
- JSON / XML Processing
- Nice to Have
- Streamlit
- Financial Services / Banking Domain Knowledge
- Personal Attributes
- Self-motivated and proactive.
- Strong attention to detail.
- Comfortable working within a small, high-performing team.
- Able to balance day-to-day delivery with longer-term platform improvements.
- Strong ownership mindset and willingness to take initiative.
- Competitive salary (dependent on experience)
- Private medical insurance for you (and your partner)
- Private Dental
- 10% Employer pension contribution
- 30-day annual leave entitlement plus Bank/Public Holidays
- Free Gym Membership
- Discretionary annual bonus
- Discretionary share awards
- Life Assurance
- Income Protection
- Save As You Earn company share acquisition scheme
- Tax-efficient salary sacrifice scheme to obtain bicycles and electric vehicles
- 4 days per year volunteering opportunities to support our local communities
- World class offices based in lively Ancoats
- #J-18808-Ljbffr
Data Engineer employer: DF Capital
At DF Capital, we pride ourselves on being an exceptional employer, offering a vibrant work culture in the heart of Manchester. Our commitment to employee growth is evident through comprehensive training and support, alongside a generous benefits package that includes private medical insurance, a substantial pension contribution, and ample annual leave. Join us to be part of a collaborative team that values innovation and community engagement, all while making a meaningful impact in the financial sector.
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 DF Capital!
✨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 DF Capital.
✨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 DF Capital.
✨Apply Directly through Our Website
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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 DF Capital, 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 DF Capital. 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 DF Capital
✨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 DF Capital!
✨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.
