At a Glance
- Tasks: Lead the design and implementation of QA frameworks for data pipelines.
- Company: Join a dynamic team in a fast-paced, data-driven environment.
- Benefits: Competitive contract rate, flexible work arrangements, and growth opportunities.
- Other info: Greenfield opportunity to define testing strategies and mentor others.
- Why this job: Make a real impact by ensuring data quality and reliability.
- Qualifications: Strong experience in testing ETL/ELT pipelines and advanced SQL skills.
The predicted salary is between 30000 - 40000 € per year.
Start Day: ASAP
Contract Rate: £460 per day inside IR35
Duration: 6 to 12 months initially
Role Overview
Our client is seeking a Data Engineer with strong data quality and testing expertise to lead the design and implementation of QA frameworks for business‑critical ETL/ELT pipelines. This is a greenfield opportunity to define testing strategy and build scalable, automation‑first solutions in a fast‑paced, data‑driven environment. You’ll work across the full data lifecycle, ensuring accuracy and reliability of outputs including APIs, Excel reports, and XML files. Leveraging tools such as Databricks, Python (Pytest, Pandas), and GitHub Actions, you will establish best practices, improve data trust, and enable high‑quality data delivery.
Key Responsibilities
- Own and define end‑to‑end testing strategy for data pipelines
- Build scalable automation frameworks using Python and Pytest
- Develop SQL‑based validation for reconciliation and data integrity
- Automate Excel validation using Pandas and OpenPyXL
- Validate XML outputs using lxml and xmlschema
- Embed testing into CI/CD pipelines with GitHub Actions
- Create clear logging and reporting for fast issue resolution
- Collaborate with data engineers to improve pipeline quality
- Mentor team members and establish QA best practices
Skills & Experience
- Strong experience testing ETL/ELT data pipelines
- Advanced SQL for validation and debugging
- Experience with Pandas and OpenPyXL for Excel validation
- API testing with Postman/Newman
- CI/CD experience using GitHub Actions
- Familiarity with Databricks or similar platforms
- Strong understanding of data quality and validation principles
- Experience building QA processes and mentoring others
- Exposure to cloud‑based data platforms
- Experience with tools like Great Expectations
- Knowledge of Airflow or ADF
- End‑to‑end validation across pipelines, APIs, and files
- Experience scaling QA practices in data teams
Data Engineer in Stevenage employer: Queen Square Recruitment
Join a forward-thinking company that values innovation and collaboration, where as a Data Engineer, you will have the opportunity to shape the future of data quality in a dynamic environment. With a strong emphasis on employee growth, you will benefit from mentorship opportunities and the chance to work with cutting-edge technologies like Databricks and Python. Our inclusive work culture fosters creativity and encourages you to take ownership of your projects, making it an ideal place for those seeking meaningful and rewarding employment.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer in Stevenage
✨Tip Number 1
Network like a pro! Reach out to your connections in the data engineering field and let them know you're on the lookout for opportunities. You never know who might have a lead or can refer you to a hiring manager.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving ETL/ELT pipelines and automation frameworks. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge. Be ready to discuss your experience with tools like Python, SQL, and GitHub Actions. Practising common interview questions can help you feel more confident when it’s time to shine.
✨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, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Data Engineer in Stevenage
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Data Engineer role. Highlight your experience with ETL/ELT pipelines, data quality, and any relevant tools like Python and SQL. We want to see how your skills match what we're looking for!
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 makes you a great fit for our team. Keep it concise but impactful – we love a good story!
Showcase Your Projects:If you've worked on any cool projects related to data pipelines or QA frameworks, make sure to mention them. We’re interested in seeing how you’ve applied your skills in real-world scenarios, so don’t hold back!
Apply Through Our Website:We encourage you to apply through our website for a smoother process. It helps us keep track of applications and ensures you get all the updates directly from us. Plus, it’s super easy!
How to prepare for a job interview at Queen Square Recruitment
✨Know Your Tools Inside Out
Make sure you’re well-versed in the tools mentioned in the job description, like Databricks, Python, and GitHub Actions. Brush up on your SQL skills too, as you'll likely be asked to demonstrate your ability to validate and debug data pipelines during the interview.
✨Showcase Your Testing Strategy
Prepare to discuss your approach to defining end-to-end testing strategies for ETL/ELT pipelines. Think about specific examples where you've built scalable automation frameworks or improved data quality, and be ready to explain how you did it.
✨Demonstrate Collaboration Skills
Since this role involves working closely with other data engineers, be prepared to talk about your experience collaborating on projects. Share examples of how you’ve mentored team members or established QA best practices in previous roles.
✨Prepare for Technical Questions
Expect technical questions that test your knowledge of data quality principles and validation techniques. You might be asked to solve a problem on the spot, so practice coding challenges related to data validation using Python and SQL to boost your confidence.
