At a Glance
- Tasks: Design and build scalable data pipelines using Python, SQL, and Apache Airflow.
- Company: Established bank with a focus on data engineering and analytics.
- Benefits: Competitive salary, hands-on experience, and opportunities for professional growth.
- Other info: Work in a controlled environment with excellent career advancement opportunities.
- Why this job: Join a dynamic team and make an impact in the banking sector with your data skills.
- Qualifications: Strong experience in data engineering, Python, SQL, and familiarity with BI tools.
The predicted salary is between 60000 - 75000 £ per year.
An established bank is looking for a hands-on Data Engineer to help design, build and maintain a scalable on-premise data warehouse and modern data engineering platform. This is a strong opportunity for someone who enjoys building robust data pipelines, working close to the infrastructure, and supporting business-critical analytics and reporting. The environment is non-cloud / on-prem, so this will suit someone comfortable working with Unix/Linux, scheduling, scripting, deployment and production support.
You will work with Python, SQL, Apache Airflow and dbt, while also supporting a wider Microsoft BI environment including SSIS, SSRS, SSAS and T-SQL. You will be responsible for designing and building reliable data pipelines, developing transformation logic, maintaining data models, and supporting the bank’s analytics and reporting platforms.
Key responsibilities include:- Designing and building ETL/ELT pipelines using Python and SQL
- Developing and orchestrating workflows using Apache Airflow
- Building and maintaining dbt models, macros, tests and documentation
- Working in a Unix/Linux environment for scheduling, scripting and deployment
- Supporting CI/CD pipelines and version control processes
- Translating business requirements into clear technical specifications
- Administering and supporting data analytics platforms
- Building and maintaining solutions across SSIS, SSRS, SSAS and T-SQL
- Supporting dashboards, reporting and visualisation requirements
- Performing testing, troubleshooting and issue resolution
- Producing clear technical documentation
- Working closely with stakeholders across technology, data, analytics and business teams
- Operating in line with the bank’s risk, compliance and change-control frameworks
The ideal candidate
You do not need to tick every box, but you should have strong hands-on data engineering experience and be comfortable working in a controlled, production-focused environment. We are particularly interested in people with experience across:
- Strong Python programming for data pipelines, APIs and scripting
- Advanced SQL, ideally T-SQL or PL/SQL
- Apache Airflow, including DAG configuration, maintenance and optimisation
- dbt, including models, macros, tests and documentation
- ETL/ELT design and data warehousing
- On-premise or infrastructure-aware data platforms
- CI/CD, version control and test automation
- Docker or containerisation
- Microsoft BI stack: SSIS, SSRS, SSAS and T-SQL
- Power BI, Tableau, Qlik or similar reporting/visualisation tools
Banking or financial services experience would be useful, particularly if you have worked in a regulated environment with strong governance, auditability, data quality and change-control requirements. However, strong hands-on data engineering experience is the priority.
Good fit for someone who is:
- Strong technically, but able to work with business stakeholders
- Used to controlled environments where documentation, testing and governance matter
- Comfortable with both modern data engineering tooling and established BI platforms
- Interested in building reliable, scalable data solutions rather than just dashboards
Banking Data Engineer: Python, SQL, Airflow & dbt employer: Rothstein Recruitment
Join an established bank that values innovation and technical expertise, offering a dynamic work environment where you can thrive as a Data Engineer. With a strong focus on employee growth, the bank provides opportunities for professional development and encourages collaboration across teams to drive impactful analytics and reporting solutions. Enjoy the benefits of working in a controlled, production-focused setting while contributing to meaningful projects that support the bank's strategic goals.
StudySmarter Expert Advice🤫
We think this is how you could land Banking Data Engineer: Python, SQL, Airflow & dbt
✨Tip Number 1
Network like a pro! Reach out to folks in the banking and data engineering space on LinkedIn. Join relevant groups, attend meetups, and don’t be shy about asking for informational interviews. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data pipelines, ETL processes, or any projects using Python, SQL, and Airflow. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for those technical interviews! Brush up on your Python and SQL skills, and be ready to discuss your experience with dbt and Apache Airflow. Practice explaining your thought process when solving problems, as this is often just as important as the solution itself.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got some fantastic opportunities waiting for you, and applying directly can sometimes give you a leg up. Plus, it’s super easy to keep track of your applications that way!
We think you need these skills to ace Banking Data Engineer: Python, SQL, Airflow & dbt
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience with Python, SQL, and data engineering tools like Apache Airflow and dbt. We want to see how your skills match the job description, so don’t be shy about showcasing relevant projects!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you’re passionate about data engineering and how your background fits with our needs. We love seeing enthusiasm and a bit of personality in your application.
Showcase Your Problem-Solving Skills:In your application, mention specific challenges you've faced in previous roles and how you tackled them. We’re looking for someone who can build reliable data pipelines and troubleshoot issues effectively, so let us know how you’ve done this before!
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’re considered for the role. Plus, it’s super easy – just follow the prompts and submit your materials!
How to prepare for a job interview at Rothstein Recruitment
✨Know Your Tech Stack
Make sure you’re well-versed in Python, SQL, and Apache Airflow. Brush up on your knowledge of dbt and the Microsoft BI stack too. Be ready to discuss how you've used these technologies in past projects, as this will show your hands-on experience.
✨Understand the Banking Environment
Familiarise yourself with the banking sector's data governance and compliance requirements. Knowing how to operate within a regulated environment can set you apart from other candidates. Be prepared to share examples of how you've navigated similar challenges in previous roles.
✨Demonstrate Problem-Solving Skills
Expect technical questions that assess your troubleshooting abilities. Think of specific instances where you resolved issues in data pipelines or during deployment. Highlight your approach to testing and documentation, as these are crucial in a controlled environment.
✨Engage with Stakeholders
Show that you can communicate effectively with both technical teams and business stakeholders. Prepare to discuss how you translate business requirements into technical specifications. This will demonstrate your ability to bridge the gap between tech and business needs.
