At a Glance
- Tasks: Lead the design and delivery of modern data engineering capabilities.
- Company: Inclusive tech company focused on customer commitment and future innovation.
- Benefits: Competitive salary, flexible working, and opportunities for professional growth.
- Other info: Dynamic environment with a focus on collaboration and knowledge sharing.
- Why this job: Shape the future of data engineering and drive impactful change.
- Qualifications: Proven leadership in data engineering and strong technical skills.
The predicted salary is between 120000 - 150000 € per year.
Inclusive – we succeed together
Trusting – we choose to trust each other
Customer committed – we put customers at the heart of our decisions
Future Focused – we accelerate change
Curious – we turn knowledge into action
Role Summary
Defining, building, and scaling a modern, enterprise-wide data engineering capability within a federated operating model. This role will lead the design and delivery of robust, secure, and high-performing data. The VP of Data Engineering will establish enabling the development of AI-ready data ecosystems, including knowledge graphs, ontologies, and semantically enriched datasets that support advanced analytics, machine learning, and AI-native applications. Best-in-class engineering practices, enabling domain-oriented data ownership while ensuring consistency through shared standards, governance, and platform capabilities.
A critical aspect of the role is Role Responsibilities
Champion the creation and integration of knowledge graphs and ontologies to enhance data discoverability, interoperability, and contextual understanding.
Key Skills and Experience
- Proven experience leading large-scale data engineering organizations in complex, federated or matrixed environments
- Strong hands-on and architectural experience with Snowflake/dbt/Airflow, including performance optimization, data modelling, and cost management
- Experience designing and operationalizing data governance frameworks in a federated or data mesh environment with self-service and trusted data capabilities
- Practical experience with knowledge graphs, ontologies, semantic modelling (e.g. RDF, OWL), delivering faster insights
- Strong leadership, stakeholder management, and communication skills, with the ability to influence at executive level and drive organizational change.
VP Data Engineering employer: Wood Mackenzie Ltd
As a VP of Data Engineering, you will join a forward-thinking organisation that prioritises inclusivity and collaboration, ensuring that we succeed together. Our commitment to employee growth is evident through our focus on innovative practices and the development of AI-ready data ecosystems, providing you with unique opportunities to lead transformative projects in a dynamic environment. Located in a vibrant area, we foster a culture of trust and curiosity, empowering you to turn knowledge into action while making a meaningful impact on our customers and the future of data engineering.
StudySmarter Expert Advice🤫
We think this is how you could land VP Data Engineering
✨Tip Number 1
Network like a pro! Reach out to connections in the data engineering field, especially those who work at companies you're interested in. A friendly chat can open doors and give you insider info on job openings.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving knowledge graphs and AI-ready data ecosystems. This will help you stand out and demonstrate your hands-on experience.
✨Tip Number 3
Prepare for interviews by brushing up on your leadership and stakeholder management skills. Be ready to discuss how you've influenced change in previous roles and how you can do the same with us at StudySmarter.
✨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 genuinely interested in joining our team.
We think you need these skills to ace VP Data Engineering
Some tips for your application 🫡
Show Your Passion for Data:When writing your application, let your enthusiasm for data engineering shine through! We want to see how your experience aligns with our mission of building AI-ready data ecosystems. Share specific examples that highlight your skills and passion.
Tailor Your Application:Make sure to customise your application to reflect the key skills and experiences mentioned in the job description. We love seeing candidates who take the time to connect their background with what we’re looking for, especially around knowledge graphs and data governance.
Be Clear and Concise:Keep your application straightforward and to the point. We appreciate clarity, so avoid jargon unless it’s relevant. Highlight your achievements in a way that’s easy to digest, focusing on how you’ve led teams and driven change in previous roles.
Apply Through Our Website:Don’t forget to submit your application through our website! It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it shows you’re keen on joining our team at StudySmarter!
How to prepare for a job interview at Wood Mackenzie Ltd
✨Know Your Data Engineering Stuff
Make sure you brush up on your technical skills, especially around Snowflake, dbt, and Airflow. Be ready to discuss your hands-on experience and how you've optimised performance or managed costs in previous roles.
✨Showcase Your Leadership Skills
This role is all about leading large-scale data engineering teams. Prepare examples of how you've successfully managed teams in complex environments and how you've influenced change at an executive level.
✨Understand the Federated Model
Since the company operates in a federated model, be prepared to discuss your experience with data governance frameworks and how you've implemented self-service data capabilities. This will show that you can navigate their organisational structure effectively.
✨Be Curious and Customer-Focused
Demonstrate your curiosity by asking insightful questions about their data ecosystems and how they prioritise customer needs. This aligns with their values and shows you're genuinely interested in contributing to their mission.
