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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 and a collaborative team environment.
- Why this job: Be part of a dynamic team making impactful data-driven decisions.
- Qualifications: 5+ years in data engineering with Databricks expertise required.
- Other info: Databricks Champion status is essential for this role.
The predicted salary is between 48000 - 72000 £ per year.
About the Role
We’re looking for a Databricks Champion 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
- 5+ years in data engineering with hands-on Databricks experience
- Databricks Champion Status (Solution Architect / Partner)
- Proficient in Databricks, Delta Lake, Spark, Python, SQL
- Cloud experience (Azure preferred, AWS/GCP a plus)
- Strong problem-solving and communication skills
Contact Detail:
TechYard Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer (Databricks Champion)
✨Tip Number 1
Make sure to showcase your Databricks Champion status in conversations and networking events. This will help you stand out as a qualified candidate and demonstrate your expertise in the field.
✨Tip Number 2
Engage with the Databricks community online. Participate in forums, webinars, and local meetups to connect with other professionals and learn about the latest trends and best practices in data engineering.
✨Tip Number 3
Familiarise yourself with the specific cloud platforms mentioned in the job description, especially Azure. Having hands-on experience or certifications can give you an edge when discussing your skills with our team.
✨Tip Number 4
Prepare to discuss real-world examples of how you've optimised data pipelines and managed Databricks clusters. Being able to articulate your problem-solving process will impress us during the interview.
We think you need these skills to ace Data Engineer (Databricks Champion)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your 5+ years of experience in data engineering, specifically focusing on your hands-on experience with Databricks. Include relevant projects and technologies like Delta Lake, Spark, Python, and SQL.
Craft a Compelling Cover Letter: In your cover letter, express your passion for data engineering and detail your journey to becoming a Databricks Champion. Mention specific examples of how you've designed and optimised data pipelines in previous roles.
Showcase Collaboration Skills: Since the role involves working with various teams, emphasise your collaboration skills. Provide examples of how you've successfully worked with data scientists, architects, and analysts to deliver data solutions.
Highlight Cloud Experience: If you have experience with cloud platforms, especially Azure, make sure to highlight this in your application. Discuss any cloud-native solutions you've built and how they contributed to project success.
How to prepare for a job interview at TechYard
✨Showcase Your Databricks Expertise
Make sure to highlight your hands-on experience with Databricks during the interview. Be prepared to discuss specific projects where you've developed ETL/ELT pipelines and how you optimised them for performance.
✨Demonstrate Problem-Solving Skills
Expect to face technical questions that assess your problem-solving abilities. Prepare examples of challenges you've encountered in data engineering and how you resolved them, particularly in relation to Databricks and cloud environments.
✨Communicate Effectively
Strong communication skills are essential for this role. Practice explaining complex technical concepts in simple terms, as you'll need to collaborate with various teams, including data scientists and analysts.
✨Familiarise Yourself with Data Governance
Since implementing data governance and quality best practices is a key responsibility, brush up on these topics. Be ready to discuss how you've ensured data quality in past projects and your approach to maintaining compliance.
