At a Glance
- Tasks: Build and scale QA/testing capabilities for complex ETL pipelines.
- Company: Gazelle Global, a leader in pharma data solutions.
- Benefits: Competitive salary, flexible working hours, and opportunities for skill development.
- Other info: Exciting opportunity to work with cutting-edge tools like Databricks.
- Why this job: Join a modern data environment and make a real impact on data reliability.
- Qualifications: Strong ETL/ELT experience, advanced SQL, Python skills, and CI/CD knowledge.
The predicted salary is between 50000 - 65000 € per year.
Gazelle Global is seeking a Data Engineer to build and scale QA/testing capabilities across complex ETL pipelines in Greater London. In this hands-on role, you will own the automation strategy, enhance data reliability, and integrate testing into CI/CD pipelines.
Required skills include:
- Strong ETL/ELT experience
- Advanced SQL
- Python skills
- Knowledge of CI/CD processes using GitHub Actions
The position offers the chance to work within a modern data environment, utilizing tools like Databricks.
Data Engineer & QA — Pharma Data Pipelines & Automation employer: Gazelle Global
Gazelle Global is an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration in the heart of Greater London. Employees benefit from a modern data environment, ample opportunities for professional growth, and a commitment to work-life balance, making it an ideal place for those looking to make a meaningful impact in the pharmaceutical data sector.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer & QA — Pharma Data Pipelines & Automation
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your ETL pipelines, automation projects, or any relevant work. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your SQL and Python skills. Practice common data engineering scenarios and be ready to discuss how you've tackled challenges in past projects. Confidence is key!
✨Tip Number 4
Don't forget to apply through our website! We make it easy for you to find roles that match your skills and interests. Plus, it shows you're genuinely interested in joining our team.
We think you need these skills to ace Data Engineer & QA — Pharma Data Pipelines & Automation
Some tips for your application 🫡
Show Off Your Skills:Make sure to highlight your strong ETL/ELT experience and advanced SQL and Python skills in your application. We want to see how you can bring your expertise to our team!
Tailor Your Application:Don’t just send a generic application! Tailor your CV and cover letter to reflect the specific requirements of the Data Engineer role. We love seeing how you connect your experience to what we’re looking for.
Be Clear and Concise:When writing your application, keep it clear and to the point. We appreciate straightforward communication, so make sure your key points stand out without unnecessary fluff.
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 don’t miss any important updates from our team!
How to prepare for a job interview at Gazelle Global
✨Know Your ETL/ELT Inside Out
Make sure you can discuss your experience with ETL and ELT processes in detail. Be ready to share specific examples of how you've built or scaled these pipelines, as well as any challenges you've faced and how you overcame them.
✨Show Off Your SQL and Python Skills
Prepare to demonstrate your advanced SQL and Python skills during the interview. You might be asked to solve a problem on the spot, so brush up on your coding abilities and be ready to explain your thought process clearly.
✨Understand CI/CD Processes
Familiarise yourself with CI/CD practices, especially using GitHub Actions. Be prepared to discuss how you've integrated testing into these pipelines in previous roles, as this will show your hands-on experience and understanding of automation strategies.
✨Get Acquainted with Databricks
Since the role involves working within a modern data environment, it’s a good idea to have some knowledge of Databricks. If you’ve used it before, share your experiences; if not, do a bit of research to understand its functionalities and how it fits into data engineering.
