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, professional development, and a chance to work in a dynamic environment.
- Other info: Great opportunity for career growth in a regulated financial environment.
- Why this job: Make a real impact by supporting critical analytics and reporting in the banking sector.
- Qualifications: Hands-on 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
Data Engineer - Python, SQL, Airflow, dbt - Banking employer: Rothstein Recruitment
As a leading bank, we pride ourselves on fostering a collaborative and innovative work environment where data engineers can thrive. Our commitment to employee growth is evident through continuous training opportunities and a supportive culture that values technical expertise and teamwork. Located in a dynamic financial hub, we offer competitive benefits and the chance to work on impactful projects that drive our business forward.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer - Python, SQL, Airflow, dbt - Banking
✨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, or 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 an edge. Plus, it’s super easy to keep track of your applications that way!
We think you need these skills to ace Data Engineer - Python, SQL, Airflow, dbt - Banking
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience with Python, SQL, and Apache Airflow. We want to see how your skills match the job description, so don’t be shy about showcasing your hands-on data engineering 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 banking environment. We love seeing enthusiasm and a bit of personality!
Showcase Your Technical Skills:When filling out your application, be specific about your technical skills. Mention your experience with ETL/ELT processes, dbt, and any work in Unix/Linux environments. We’re looking for those details that set you apart!
Apply Through Our Website:Don’t forget to apply 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 to do!
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 ETL/ELT processes and be ready to discuss how you've built data pipelines in the past. The more specific examples you can provide, the better!
✨Understand the Banking Environment
Familiarise yourself with the banking sector's regulations and compliance requirements. Be prepared to talk about how you’ve navigated these in previous roles, especially regarding data governance and quality.
✨Showcase Your Problem-Solving Skills
Expect to face technical challenges during the interview. Think of scenarios where you had to troubleshoot or optimise a data pipeline. Highlight your approach to problem-solving and how you ensure reliability in your solutions.
✨Communicate with Stakeholders
Since you'll be working closely with various teams, demonstrate your ability to translate technical jargon into business language. Share experiences where you successfully collaborated with non-technical stakeholders to meet their data needs.
