VP Data Engineering

• Define and execute the enterprise data engineering strategy aligned to a federated (data mesh-style) operating model, balancing domain autonomy with centralized governance.
• Build, scale, and lead a high-performing data engineering organization, including platform, enablement, and domain-aligned teams.
• Architect and oversee scalable, secure data platforms leveraging AWS services, dbt, and Snowflake.
• Enable AI-ready data ecosystems, including knowledge graphs, ontologies, and semantically enriched datasets.

This role enables Wood Mackenzie to deliver a clear, interconnected view of the entire energy value chain, empowering customers to identify risks sooner, spot opportunities faster, and recalibrate strategy with confidence, ultimately accelerating the transition to a more sustainable energy future.

• Proven experience leading large-scale data engineering organizations in complex, federated or matrixed environments.
• Deep expertise in AWS data ecosystem (S3, Glue, Lambda, Kinesis, EMR, IAM, Lake Formation) and cloud-native architecture patterns.
• 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.

Compensation and perks not specified in the job posting. Wood Mackenzie offers an inclusive, trusting, customer-committed, future-focused, and curious culture.

Wood Mackenzie is the global leader in analytics, insights, and proprietary data across the entire energy and natural resources landscape, guiding the decisions of the world’s most influential energy producers, utilities, financial institutions, and governments.