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- Tasks: Lead a team of eight engineers in data transformation projects.
- Company: Join a top supply chain organisation driving digital innovation.
- Benefits: Enjoy a competitive salary and flexible work options.
- Why this job: Be part of a dynamic team shaping the future of data engineering.
- Qualifications: 6+ years in data engineering with recent managerial experience required.
- Other info: Referral bonuses available for successful candidate introductions.
The predicted salary is between 65000 - 70000 £ per year.
Salary: £65,000- £70,000 per annum
Location: Leeds (One day on site).
VIQU have partnered with a leading supply chain organisation who are looking to expand their data teams. The Data Engineering Manager will manage a team of eight to help with an on-going digital transformation. The ideal candidate will come from a technical background but has recently worked in a managerial role focused on mentoring, coaching, reviewing code, and standard setting.
The role will focus on the development of the clients Databricks platform (AWS is preferred but open to Azure.GCP experience also), utilising Python and SQL, contribute to CI/CD pipelines, strategy development, cost optimisation and data governance frameworks.
Job duties of the Data Engineering Manager:
- Manage a team of eight engineers, helping to mentor and coach the team.
- Manage the adoption of automated CI/CD pipelines.
- Implement a new delivery roadmap.
- Contribute to the development of a new Databricks system in AWS (AWS experience is preferred but they are open to managers with Azure experience).
- Cost optimisation.
- Establish data governance frameworks for secure handling of delivery information.
Requirements of the Data Engineering Manager:
- 6+ years experience in a hands on data engineer role, with over a years recent experience in a managerial role, coaching similar sized teams.
- Deep knowledge of the Databricks platform.
- Hands on Python development experience.
- SQL optimisation.
- Experience with large scale data pipeline optimisation.
- Experience with Streaming and Batch Spark workloads.
- Strong people management skills.
To discuss this exciting opportunity in more detail, please APPLY NOW for a no obligation chat with your VIQU Consultant.
If you know someone who would be ideal for this role, by way of showing our appreciation, VIQU is offering an introduction fee up to £1,000 once your referral has successfully started work with our client (terms apply).
To be the first to hear about other exciting opportunities, technology, and recruitment news, please also follow us at ‘VIQU IT Recruitment’ on LinkedIn, and Twitter: @VIQU_UK.
Data Engineering Manager (Leeds) employer: VIQU IT Recruitment
Contact Detail:
VIQU IT Recruitment Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineering Manager (Leeds)
✨Tip Number 1
Familiarise yourself with the Databricks platform, especially if you have experience in AWS, Azure, or GCP. Being able to discuss specific projects or features you've worked on will show your expertise and make you stand out.
✨Tip Number 2
Highlight your leadership skills by preparing examples of how you've successfully mentored and coached teams in the past. Be ready to discuss your approach to managing a team of engineers and how you foster collaboration.
✨Tip Number 3
Brush up on your knowledge of CI/CD pipelines and be prepared to share your experiences in implementing them. Discussing specific challenges you've faced and how you overcame them can demonstrate your problem-solving abilities.
✨Tip Number 4
Understand the importance of data governance frameworks and be ready to talk about your experience in establishing secure handling processes. This will show that you are not only technically proficient but also aware of compliance and security issues.
We think you need these skills to ace Data Engineering Manager (Leeds)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your relevant experience in data engineering and management. Focus on your hands-on experience with Databricks, Python, and SQL, as well as your leadership skills in mentoring and coaching teams.
Craft a Compelling Cover Letter: Write a cover letter that specifically addresses the requirements of the Data Engineering Manager role. Mention your experience with CI/CD pipelines, cost optimisation, and data governance frameworks to demonstrate your fit for the position.
Showcase Your Technical Skills: In your application, emphasise your technical background and any projects you've led that involved large-scale data pipeline optimisation or the development of Databricks systems. This will help you stand out as a candidate with both managerial and technical expertise.
Proofread Your Application: Before submitting your application, carefully proofread all documents for spelling and grammatical errors. A polished application reflects your attention to detail and professionalism, which are crucial for a managerial role.
How to prepare for a job interview at VIQU IT Recruitment
✨Showcase Your Technical Expertise
As a Data Engineering Manager, it's crucial to demonstrate your deep knowledge of the Databricks platform and your hands-on experience with Python and SQL. Be prepared to discuss specific projects where you've optimised data pipelines or implemented CI/CD processes.
✨Highlight Your Leadership Skills
Since the role involves managing a team of eight engineers, emphasise your experience in mentoring and coaching. Share examples of how you've successfully led teams, set standards, and fostered a collaborative environment.
✨Discuss Cost Optimisation Strategies
The job requires a focus on cost optimisation. Be ready to talk about your previous experiences where you implemented strategies that reduced costs while maintaining efficiency. This will show your potential employer that you can contribute to their bottom line.
✨Prepare for Scenario-Based Questions
Expect scenario-based questions that assess your problem-solving skills and decision-making abilities. Think of situations where you had to establish data governance frameworks or manage large-scale data pipeline challenges, and be ready to explain your thought process.
