At a Glance
- Tasks: Design and optimise data pipelines using Databricks and AWS.
- Company: Join a dynamic data engineering team at Coforge in London.
- Benefits: Competitive salary, flexible working options, and career development opportunities.
- Other info: Be part of a collaborative team focused on innovation and excellence.
- Why this job: Make an impact by developing high-performance data solutions in a cutting-edge environment.
- Qualifications: Expertise in Databricks, AWS experience, and strong problem-solving skills.
The predicted salary is between 60000 - 80000 € per year.
Coforge is seeking a highly skilled Data Engineer - Databricks to join our dynamic data engineering team in London. The role requires a strong focus on designing, developing, and optimizing data pipelines leveraging Databricks and AWS.
Key responsibilities include:
- Developing high-performance data pipelines
- Ensuring data quality
- Implementing CI/CD workflows
The ideal candidate will have expert-level skills in Databricks, AWS experience, and excellent problem-solving abilities.
Hybrid Databricks Data Engineer – AWS, PySpark & Delta Lake employer: Coforge
Coforge is an exceptional employer that fosters a collaborative and innovative work culture, making it an ideal place for Data Engineers to thrive. Located in the vibrant city of London, employees benefit from a dynamic environment that encourages professional growth through continuous learning opportunities and exposure to cutting-edge technologies like Databricks and AWS. With a strong commitment to employee well-being and a focus on work-life balance, Coforge stands out as a rewarding workplace for those seeking meaningful contributions in the data engineering field.
StudySmarter Expert Advice🤫
We think this is how you could land Hybrid Databricks Data Engineer – AWS, PySpark & Delta Lake
✨Tip Number 1
Network like a pro! Reach out to current employees at Coforge on LinkedIn or other platforms. A friendly chat can give us insights into the company culture and maybe even a referral!
✨Tip Number 2
Show off your skills! Prepare a mini-project or case study that highlights your experience with Databricks, AWS, and PySpark. This hands-on demonstration can really set us apart from the crowd.
✨Tip Number 3
Be ready for technical interviews! Brush up on your data pipeline optimisation techniques and CI/CD workflows. We want to be able to discuss our past projects confidently and showcase our problem-solving skills.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets noticed. Plus, we can tailor our CVs and cover letters to match what Coforge is looking for in a Data Engineer.
We think you need these skills to ace Hybrid Databricks Data Engineer – AWS, PySpark & Delta Lake
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience with Databricks, AWS, and PySpark. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects or achievements!
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 perfect fit for our team at Coforge. Let us know what excites you about this role!
Showcase Problem-Solving Skills:Since problem-solving is key in this role, include examples in your application that demonstrate how you've tackled challenges in data engineering. We love seeing how you think on your feet!
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!
How to prepare for a job interview at Coforge
✨Know Your Tech Inside Out
Make sure you brush up on your Databricks, AWS, and PySpark skills. Be ready to discuss specific projects where you've used these technologies, and think about the challenges you faced and how you overcame them.
✨Showcase Your Problem-Solving Skills
Prepare to share examples of how you've tackled complex data engineering problems in the past. Use the STAR method (Situation, Task, Action, Result) to structure your answers and highlight your analytical thinking.
✨Understand CI/CD Workflows
Since implementing CI/CD workflows is a key responsibility, make sure you can explain your experience with these processes. Discuss any tools you've used and how they improved your data pipeline efficiency.
✨Ask Insightful Questions
At the end of the interview, don’t forget to ask questions that show your interest in the role and the company. Inquire about the team’s current projects or how they measure success in their data pipelines. This shows you're genuinely interested and engaged.
