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- Tasks: Lead the design and delivery of innovative data solutions and drive organisational change.
- Company: Join Wood Mackenzie Ltd, a leader in data engineering based in Edinburgh.
- Benefits: Competitive salary, leadership opportunities, and a chance to shape the future of data.
- Other info: Exciting opportunity for growth in a dynamic and collaborative environment.
- Why this job: Make a significant impact by building modern data capabilities and knowledge graphs.
- Qualifications: Proven experience in large-scale data engineering and strong skills in Snowflake, dbt, and Airflow.
The predicted salary is between 80000 - 100000 £ per year.
Wood Mackenzie Ltd in Edinburgh is seeking a VP of Data Engineering to define, build, and scale a modern data engineering capability. This role involves leading the design and delivery of data solutions, establishing governance frameworks, and driving organizational change.
The ideal candidate will have proven experience in large-scale data engineering, strong hands-on skills in Snowflake, dbt, Airflow, and a solid understanding of knowledge graphs. The position emphasizes leadership and communication skills.
VP, Data Engineering — AI-Ready Data & Knowledge Graphs in Edinburgh employer: Wood Mackenzie Ltd
Contact Detail:
Wood Mackenzie Ltd Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land VP, Data Engineering — AI-Ready Data & Knowledge Graphs in Edinburgh
✨Tip Number 1
Network like a pro! Reach out to folks in your industry on LinkedIn or at events. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! If you’ve got hands-on experience with Snowflake, dbt, or Airflow, consider creating a portfolio or blog to showcase your projects. It’s a great way to stand out!
✨Tip Number 3
Prepare for interviews by practising common questions and scenarios related to data engineering. We recommend doing mock interviews with friends or using online platforms to get comfortable.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive!
We think you need these skills to ace VP, Data Engineering — AI-Ready Data & Knowledge Graphs in Edinburgh
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the specific skills and experiences mentioned in the job description. Highlight your hands-on experience with Snowflake, dbt, and Airflow, as well as any leadership roles you've held.
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're the perfect fit for the VP of Data Engineering role. Share your vision for building modern data capabilities and how you can drive organisational change.
Showcase Your Leadership Skills: Since this role emphasises leadership, be sure to include examples of how you've successfully led teams or projects in the past. We want to see your communication style and how you inspire others.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy!
How to prepare for a job interview at Wood Mackenzie Ltd
✨Know Your Tech Inside Out
Make sure you’re well-versed in Snowflake, dbt, and Airflow. Brush up on your hands-on skills and be ready to discuss specific projects where you've used these tools. This will show that you not only understand the theory but can also apply it practically.
✨Showcase Your Leadership Skills
As a VP, you'll need to demonstrate strong leadership capabilities. Prepare examples of how you've led teams through change or implemented governance frameworks in previous roles. Highlight your communication style and how you motivate others.
✨Understand Knowledge Graphs
Since this role involves knowledge graphs, make sure you can explain what they are and how they can be leveraged in data engineering. Be prepared to discuss any relevant experience you have with them and how they can drive organisational change.
✨Prepare for Scenario-Based Questions
Expect questions that ask how you would handle specific challenges in data engineering. Think about scenarios involving scaling data solutions or overcoming governance issues. Practising your responses will help you articulate your thought process clearly during the interview.