Senior Analytics Engineer

• Design, develop, and maintain complex, scalable, and reusable data models and transformation layers in Snowflake using dbt, translating analytical and business requirements into robust multi-domain data structures.
• Own and optimize data transformation workflows to ensure analytics data is reliable, well-structured, and delivered to agreed quality and timeliness standards.
• Provide technical direction, coaching, and mentoring to Analytics Engineers and Data Analysts, acting as an internal subject matter expert for dbt and analytics engineering best practices.
• Collaborate with data engineers, research, and business stakeholders to shape requirements and deliver high-impact analytics solutions.

This role enables data-driven decision-making in the energy and natural resources sector, helping organizations identify risks, spot opportunities, and recalibrate strategies to accelerate the transition to a more sustainable energy system.

• 5+ years of hands-on experience in analytics engineering or a closely related data-focused role, with proven experience in data modelling and transformation.
• Expert-level SQL skills, with demonstrated experience designing and optimising complex analytical data models.
• Proven experience working with Snowflake and strong practical experience using dbt in a production analytics environment.
• Strong understanding of Kimball dimensional modelling, including star schemas, conformed dimensions, and slowly changing dimension patterns.

Compensation and perks not specified in the 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 decisions of the world’s most influential energy producers, utilities, financial institutions, and governments for over 50 years.