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: Join a collaborative team focused on building reliable data solutions.
- Why this job: Make a real impact by supporting critical analytics in a dynamic banking environment.
- Qualifications: Strong experience in data engineering, Python, SQL, and familiarity with Unix/Linux.
The predicted salary is between 60000 - 80000 € 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
- Unix/Linux environments
- 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:
- A practical, hands-on Data Engineer
- Comfortable owning production data pipelines
- 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 in Slough employer: Rothstein Recruitment
Join an established bank that values innovation and collaboration, 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 a culture of continuous learning. Enjoy the unique advantage of working in a non-cloud, on-premise setting, allowing you to engage deeply with infrastructure while contributing to critical business analytics and reporting.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer - Python, SQL, Airflow, dbt - Banking in Slough
✨Network Like a Pro
Get out there and connect with people in the banking and data engineering space. Attend meetups, webinars, or even just grab a coffee with someone in the industry. You never know who might have the inside scoop on job openings!
✨Show Off Your Skills
When you get the chance to chat with potential employers, don’t hold back! Share your hands-on experience with Python, SQL, and Apache Airflow. Talk about the data pipelines you've built and how you've tackled challenges in production environments.
✨Tailor Your Approach
Make sure to tailor your conversations and presentations to highlight your experience with on-premise data solutions and CI/CD processes. Show them you understand their needs and can hit the ground running in their controlled environment.
✨Apply Through Our Website
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive and take that extra step!
We think you need these skills to ace Data Engineer - Python, SQL, Airflow, dbt - Banking in Slough
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience with Python, SQL, and data engineering tools like 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 banking environment. Keep it concise but engaging – we love a good story!
Showcase Your Technical Skills:When filling out your application, make sure to mention specific technologies you’ve worked with, especially those listed in the job description. We’re keen on seeing your hands-on experience with ETL processes and data pipelines.
Apply Through Our Website:We encourage you to apply directly through our website for the best chance of getting noticed. It’s super easy, and you’ll be able to track your application status. Plus, we love seeing candidates who take that extra step!
How to prepare for a job interview at Rothstein Recruitment
✨Know Your Tech Stack
Make sure you’re well-versed in Python, SQL, Apache Airflow, and dbt. 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 if you’ve worked in a controlled environment before.
✨Showcase Your Problem-Solving Skills
Be ready to discuss challenges you've faced in data engineering and how you resolved them. Whether it’s troubleshooting a data pipeline or optimising a workflow in Airflow, concrete examples will demonstrate your hands-on experience.
✨Communicate with Stakeholders
Highlight your ability to translate technical jargon into business language. Discuss how you’ve collaborated with different teams, ensuring that everyone is on the same page regarding data requirements and project goals.
