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For Companies At a Glance
- Tasks: Design and build a cloud-based enterprise data warehouse for critical business insights.
- Company: Join a global leader in the payments industry, committed to innovation and growth.
- Benefits: Enjoy fully remote work, flexibility, and a strong focus on work-life balance.
- Why this job: Shape the future of data with autonomy in a supportive, empowering culture.
- Qualifications: Bachelor's degree in a technical field and 4+ years of relevant experience required.
- Other info: Opportunity for mentorship and continuous learning in a dynamic environment.
The predicted salary is between 43200 - 72000 £ per year.
The RoleAs 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 doneProvide 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 QueriesETL 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 streamsThis role may require additional duties and/or assignments as designated by management. #J-18808-Ljbffr
Data Engineer employer: JobLeads GmbH
Contact Detail:
JobLeads GmbH Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer
✨Tip Number 1
Familiarise yourself with the specific methodologies mentioned in the job description, such as Kimball and Data Vault. Being able to discuss these frameworks in detail during an interview will demonstrate your expertise and alignment with the company's needs.
✨Tip Number 2
Showcase your experience with cloud-based platforms like Snowflake. If you have worked on similar projects, be prepared to share specific examples of how you designed and implemented data solutions that improved business outcomes.
✨Tip Number 3
Highlight your leadership skills and experience mentoring others. Since this role involves providing guidance to colleagues, being able to articulate your past experiences in leading teams or projects will set you apart from other candidates.
✨Tip Number 4
Prepare to discuss your problem-solving approach, especially in relation to data quality and integrity. Be ready to provide examples of challenges you've faced in previous roles and how you overcame them, as this will showcase your proactive mindset.
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, particularly with cloud-based enterprise data warehouses and the specific technologies mentioned in the job description, such as SQL, Python, and DBT.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for building data platforms and your ability to lead projects. Mention specific examples of past projects where you designed or implemented data solutions.
Highlight Technical Skills: Clearly list your technical skills related to the role, including your experience with ETL/ELT processes, data modelling, and any familiarity with tools like Snowflake or CI/CD practices. Use bullet points for clarity.
Showcase Collaboration Experience: Since the role involves working with cross-functional teams, include examples of how you've successfully collaborated with other departments in previous roles. This could be through projects or initiatives that required teamwork.
How to prepare for a job interview at JobLeads GmbH
✨Showcase Your Technical Skills
Be prepared to discuss your experience with SQL, Python, and data modelling in detail. Bring examples of past projects where you've designed ETL pipelines or worked with cloud analytics platforms like Snowflake.
✨Demonstrate Problem-Solving Abilities
Expect to face scenario-based questions that assess your troubleshooting skills. Think of specific challenges you've encountered in previous roles and how you resolved them, showcasing your proactive mindset.
✨Highlight Collaboration Experience
Since the role involves working with cross-functional teams, be ready to share examples of how you've successfully collaborated with product managers, business analysts, or engineers to deliver data solutions.
✨Prepare for Questions on Best Practices
Familiarise yourself with industry best practices for data warehousing and engineering methodologies like Kimball and Data Vault. Be ready to discuss how you would implement these in the new enterprise data warehouse.
