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For Companies At a Glance
- Tasks: Join our global team to optimise data pipelines and support cross-functional teams.
- Company: Wolfspeed is a leader in innovative data solutions, committed to excellence and teamwork.
- Benefits: Enjoy flexible work options, competitive pay, and a vibrant company culture.
- Why this job: Be part of a passionate team tackling challenging projects with real-world impact.
- Qualifications: 3+ years in Data Engineering or Software Engineering with a focus on data; Python skills required.
- Other info: Eager learners are welcome; we value passion and teamwork over strict qualifications.
The predicted salary is between 36000 - 60000 £ per year.
The Role
As part of a global team you will be responsible for expanding and optimizing our data and data pipeline architecture, as well as optimizing data flow and collection for cross-functional teams. The ideal candidate is an experienced data pipeline builder and data wrangler who enjoys optimizing data solutions and building them from the ground up. The Data Engineer will support our software developers, database architects, data analysts and data scientists while ensuring optimal data delivery architecture is consistent throughout ongoing projects. The Data Engineer will be responsible for the day-to-day activities related to the implementation of new services and support for existing services.
We are looking for intelligent, driven individuals who are passionate about what they do and have exceptional teamwork skills. The skills and experience needed for this role are listed below. However, we understand that there might be a few requirements that you don’t meet or skills that you don’t yet have. That’s ok! If you are a smart, passionate, hardworking individual who is eager to learn we would like to speak with you about joining our wolf pack!
Your day-to-day – We do what others say can’t be done
- Provide technical expertise and execute the design, development and support of data solutions for Wolfspeed business partners, including configuration, administration, monitoring, performance tuning, debugging, and operationalization.
- Build and maintain data solutions using Snowflake, dbt (data build tool), Fivetran, Azure Cloud (storage, VMs, containers, Azure Data Factory), Python, Docker and SQL.
- Participate in the development lifecycle using Agile / DevOps methodologies using Azure DevOps.
- Translate simple to complex requirements into functional and actionable tasks.
- Serve as a subject matter expert for Wolfspeed operations for data integration from enterprise applications (SAP, Oracle, ModelN, Salesorce, Workday, etc.), using that knowledge to craft data solutions that provide maximum visibility to global stakeholders.
Your Profile – Ready to join the Pack?
- Minimum 3+ years’ experience in a Data Engineering role, or Software Engineering role with a focus on data.
- Hands-on skills with a programming language such as Python, Java, Go, etc.
- Public cloud experience (Azure, AWS or GCP)
- Writing complex SQL Queries
- ETL tools (Fivetran, Azure Data Factory) or writing custom data extraction applications, Data Modeling, Data Warehousing and working with large-scale datasets.
- Experience leveraging DevOps and lean development principles such as Continuous Integration, Continuous Delivery/Deployment using tools like Azure DevOps, Github, Gitlab, etc.
- Designing and building modern data pipelines and data streams
- This role may require additional duties and/or assignments as designated by management.
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Data Engineer employer: Wolfspeed
Contact Detail:
Wolfspeed Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer
✨Tip Number 1
Familiarise yourself with the specific tools mentioned in the job description, such as Snowflake, dbt, and Azure Cloud. Having hands-on experience or even personal projects using these technologies can set you apart from other candidates.
✨Tip Number 2
Showcase your teamwork skills by preparing examples of past collaborative projects. Be ready to discuss how you contributed to team success and how you handled challenges, as this role emphasises working with cross-functional teams.
✨Tip Number 3
Brush up on Agile and DevOps methodologies, as they are crucial for this position. Understanding how to work within these frameworks will demonstrate your readiness to adapt to the company's workflow.
✨Tip Number 4
Prepare to discuss your experience with data integration from enterprise applications like SAP or Oracle. Being able to articulate your knowledge in this area will show that you can provide valuable insights into data solutions for the company.
We think you need these skills to ace Data Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data engineering, programming languages like Python, and any cloud experience you have. Use keywords from the job description to ensure your application stands out.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for data engineering and your eagerness to learn. Mention specific projects or experiences that demonstrate your skills in building data pipelines and working with large datasets.
Showcase Technical Skills: In your application, clearly outline your technical skills, especially those mentioned in the job description such as SQL, ETL tools, and cloud platforms. Provide examples of how you've used these skills in previous roles.
Highlight Teamwork Experience: Since the role emphasises teamwork, include examples of how you've successfully collaborated with cross-functional teams in past projects. This will show that you can work well within their global team structure.
How to prepare for a job interview at Wolfspeed
✨Showcase Your Technical Skills
Be prepared to discuss your hands-on experience with programming languages like Python and SQL. Bring examples of data solutions you've built or optimised, and be ready to explain the technical challenges you faced and how you overcame them.
✨Understand the Tools
Familiarise yourself with the specific tools mentioned in the job description, such as Snowflake, dbt, and Azure Data Factory. If possible, demonstrate your knowledge of these tools during the interview by discussing how you've used them in past projects.
✨Emphasise Teamwork and Collaboration
Since the role involves working with cross-functional teams, highlight your teamwork skills. Share examples of how you've collaborated with software developers, data analysts, or other stakeholders to achieve project goals.
✨Prepare for Problem-Solving Questions
Expect to face scenario-based questions that assess your problem-solving abilities. Practice articulating your thought process when tackling complex data challenges, and be ready to discuss how you would approach building a data pipeline from scratch.
