Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Lead the transformation to a data-first approach, managing a Data Engineering team.
- Company: Join a global Private Equity firm focused on modernising their data strategy.
- Benefits: Enjoy opportunities for career growth and work in a dynamic, innovative environment.
- Why this job: Be part of a critical data transformation that drives business growth and insights.
- Qualifications: Experience with Python, Databricks, Azure, and managing high-performing tech teams required.
- Other info: Ideal for data enthusiasts passionate about governance and quality management.
The predicted salary is between 72000 - 108000 £ per year.
A global Private Equity firm are seeking an experienced Head of Data Engineering as part of a critical data transformation and modernisation programme, moving towards a data-first approach. They are currently in the process of replacing a legacy data-warehouse setup with a platform as a service model using Databricks hosted on Azure, which this role will be responsible for leading, taking line management responsibilities for their Data Engineering team.
You will take ownership for progressing their Databricks setup, from its current PoC/incubator phase through to production, ensuring a high level of optimisation and scalability to operate at a global scale. This will also involve implementing a semantic layer within the platform for effective data management and organisation, as well as the development of associated data pipelines and real-time reporting & visualisation capabilities.
Once the platform is in place, the business will then look to apply Data Science techniques with the aim of building a best-in-class data function that works in partnership with the Investment Team and actively provides deep, actionable insights to enable business growth.
The ideal candidate will demonstrate:
- A technical background in data engineering with experience of technologies including Python, Spark, Databricks and Azure cloud.
- Previous experience in managing the end-to-end build of an Azure Databricks platform.
- Passionate about all aspects of data (data governance, data quality management etc.) and the positive impact ‘good data’ can bring to a business.
- Demonstrable experience in setting up and managing high-performing technology teams, establishing and driving best practices and being able to still engage at a technical level.
- Able to credibly and confidently engage with the business at all levels.
- A background in Financial Services (Private Markets, Investment Banking, Investment Management) or similarly regulated industry such as Gambling/Online Gaming is critical.
If you are a data enthusiast with experience in leading high-performing teams to develop modern data platforms, then this is a genuinely exciting time to join a growing business transitioning to a data-first approach.
Head of Data Engineering employer: Cornwallis Elt
Contact Detail:
Cornwallis Elt Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Head of Data Engineering
✨Tip Number 1
Network with professionals in the data engineering field, especially those who have experience with Databricks and Azure. Attend industry meetups or webinars to connect with potential colleagues and learn about their experiences, which can give you insights into what the company values.
✨Tip Number 2
Familiarise yourself with the latest trends in data governance and data quality management. Being able to discuss these topics intelligently during interviews will demonstrate your passion for data and your understanding of its impact on business growth.
✨Tip Number 3
Prepare to showcase your leadership skills by gathering examples of how you've successfully managed high-performing teams in the past. Be ready to discuss specific challenges you faced and how you overcame them, as this will highlight your capability to lead the Data Engineering team effectively.
✨Tip Number 4
Research the company's current data transformation initiatives and be prepared to share your thoughts on how you would approach the transition to a data-first model. This shows that you're proactive and genuinely interested in contributing to their goals.
We think you need these skills to ace Head of Data Engineering
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Databricks, Azure, and data engineering. Emphasise your leadership skills and any relevant projects you've led, particularly those involving data transformation and modernisation.
Craft a Compelling Cover Letter: In your cover letter, express your passion for data and how it can positively impact a business. Mention specific examples of your previous work in managing data platforms and teams, and how you can contribute to the company's data-first approach.
Showcase Technical Skills: Clearly outline your technical expertise in Python, Spark, and ETL processes. Provide examples of how you've successfully implemented these technologies in past roles, especially in relation to building Azure Databricks platforms.
Highlight Relevant Experience: If you have a background in Financial Services or a similarly regulated industry, make sure to highlight this experience. Discuss how your knowledge of these sectors can benefit the company in their data initiatives.
How to prepare for a job interview at Cornwallis Elt
✨Showcase Your Technical Expertise
Be prepared to discuss your experience with Databricks, Azure, and Python in detail. Highlight specific projects where you've successfully implemented data engineering solutions, focusing on the challenges you faced and how you overcame them.
✨Demonstrate Leadership Skills
Since this role involves managing a team, be ready to share examples of how you've built and led high-performing teams in the past. Discuss your approach to fostering collaboration and driving best practices within your team.
✨Understand the Business Context
Research the company’s operations in Private Equity and how data can drive business growth. Be prepared to discuss how your data strategies can align with their investment goals and enhance decision-making processes.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving abilities in real-world scenarios. Think about how you would handle challenges related to data governance, quality management, and the implementation of data pipelines in a fast-paced environment.
