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For Companies At a Glance
- Tasks: Design and optimise data pipelines using Databricks for diverse clients.
- Company: Join a forward-thinking company focused on innovative data solutions.
- Benefits: Enjoy flexible work options, competitive pay, and opportunities for growth.
- Why this job: Be part of a dynamic team that values collaboration and creativity in data engineering.
- Qualifications: 3+ years in data engineering with hands-on Databricks experience required.
- Other info: Cloud experience is a plus; certifications in data engineering are preferred.
The predicted salary is between 48000 - 72000 £ per year.
We’re looking for a Data Engineer to design, build, and optimize data pipelines using Databricks. You’ll work with clients and internal teams to deliver scalable, efficient data solutions tailored to business needs.
Key Responsibilities
- Develop ETL/ELT pipelines with Databricks and Delta Lake
- Integrate and process data from diverse sources
- Collaborate with data scientists, architects, and analysts
- Optimize performance and manage Databricks clusters
- Build cloud-native solutions (Azure preferred, AWS/GCP also welcome)
- Implement data governance and quality best practices
- Automate workflows and maintain CI/CD pipelines
- Document architecture and processes
What We’re Looking For
Required:
- 3+ years in data engineering with hands-on Databricks experience
- Proficient in Databricks, Delta Lake, Spark, Python, SQL
- Cloud experience (Azure preferred, AWS/GCP a plus)
- Strong problem-solving and communication skills
Preferred:
- Experience with MLflow, Power BI/Tableau
- Cloud/Data engineering certifications
- Familiarity with CI/CD and data automation tools
Data Engineer employer: TechYard
Contact Detail:
TechYard Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer
✨Tip Number 1
Familiarise yourself with Databricks and Delta Lake by exploring their documentation and tutorials. This will not only enhance your understanding but also demonstrate your initiative and commitment to mastering the tools we use.
✨Tip Number 2
Engage with the data engineering community on platforms like LinkedIn or GitHub. Sharing your projects or insights can help you build a network and showcase your expertise, making you a more attractive candidate for us.
✨Tip Number 3
Consider contributing to open-source projects related to data engineering. This hands-on experience can bolster your skills and provide concrete examples of your work, which is invaluable when discussing your background with us.
✨Tip Number 4
Prepare to discuss specific challenges you've faced in previous roles and how you solved them using Databricks or similar technologies. This will highlight your problem-solving abilities and show us that you're ready to tackle real-world issues.
We think you need these skills to ace Data Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Databricks, Delta Lake, and any relevant cloud platforms like Azure or AWS. Use specific examples of projects where you've developed ETL/ELT pipelines or collaborated with data scientists.
Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for the role and the company. Mention how your skills align with their needs, particularly your hands-on experience with Databricks and your problem-solving abilities.
Showcase Relevant Projects: If you have worked on notable projects involving data engineering, especially using Databricks, include these in your application. Describe your role, the technologies used, and the impact of your work.
Highlight Soft Skills: Since collaboration is key in this role, emphasise your communication skills and ability to work with cross-functional teams. Provide examples of how you've successfully collaborated with data scientists or analysts in the past.
How to prepare for a job interview at TechYard
✨Showcase Your Technical Skills
Be prepared to discuss your hands-on experience with Databricks, Delta Lake, and Spark. Bring examples of past projects where you developed ETL/ELT pipelines and be ready to explain the challenges you faced and how you overcame them.
✨Demonstrate Problem-Solving Abilities
Expect technical questions that assess your problem-solving skills. Practice explaining your thought process when tackling data engineering challenges, as this will show your analytical capabilities and how you approach complex issues.
✨Highlight Collaboration Experience
Since the role involves working with data scientists, architects, and analysts, share examples of successful collaborations. Discuss how you communicated effectively with different teams to deliver data solutions that met business needs.
✨Familiarise Yourself with Cloud Solutions
As cloud experience is essential, brush up on your knowledge of Azure, AWS, and GCP. Be ready to discuss any cloud-native solutions you've built and how you managed Databricks clusters in a cloud environment.
