Senior Analytics Engineer

Responsibilities

• The successful candidate will be responsible for:
• Advanced Data Modelling and Transformation
• Platform & Workflow Leadership
• Owning and optimising data transformation workflows to ensure analytics data is reliable, well-structured, and delivered to agreed quality and timeliness standards. Proactively identifies opportunities to improve performance, scalability, and maintainability of the analytics layer.
• Technical Leadership & Enablement
• Providing technical direction, coaching, and mentoring to Analytics Engineers and Data Analysts. Acts as an internal subject matter expert for dbt, analytics engineering patterns, and modelling best practices, enabling consistent adoption across teams.
• Collaboration & Stakeholder Engagement
• Working closely with data engineers, research, and business stakeholders to shape requirements, manage expectations, and deliver high‑impact analytics solutions. Engages confidently with senior stakeholders to influence priorities.
• Analytics CI/CD & Development Practices
• Owns or contributes to the dbt CI/CD pipeline, including environment strategy, deployment automation, slim CI, and state-based model selection. Ensures analytics code follows Git-based workflows with appropriate review, testing, and promotion practices.
• Platform Cost & Performance Awareness
• Designs models and transformation strategies that balance analytical richness with Snowflake compute efficiency. Applies incremental materialisation, clustering, and warehouse sizing considerations to manage cost and query performance at scale.
• Data Quality, Governance & Standards
• Defining and implementing data quality frameworks, testing strategies, and documentation standards across analytics datasets. Acts as a champion for data governance, challenging the status quo where appropriate and raising the maturity of data practices across teams.
• Candidate Profile:
• The ideal candidate combines deep technical expertise with strong communication and leadership skills, operating as a trusted advisor within the data organisation.
• Essential Experience and Qualifications:
• A bachelor's degree in quantitative discipline such as Data Science, Computer Science, Engineering, or equivalent practical experience.
• 5+ years of hands-on experience in a

Additional Information

Wood Mackenzie is the global leader in analytics, insights and proprietary data across the entire energy and natural resources landscape. For over 50 years our work has guided the decisions of the world's most influential energy producers, utilities companies, financial institutions and governments. Now, with the world's energy system more complex and interconnected than ever before, sector-specific views are no longer enough. That's why we've redefined what's possible with Intelligence Connected. By fusing our unparalleled proprietary data with the sharpest analytical minds, all supercharged by Synoptic AI, we deliver a clear, interconnected view of the entire value chain. Our trusted team of 2,700 experts across 30 countries breaks siloes and connects industries, markets and regions across the globe. This empowers our customers to identify risk sooner, spot opportunities faster and recalibrate strategy with confidence - whether planning days, weeks, months or decades ahead. Wood Mackenzie Intelligence Connected WoodMac.com Wood Mackenzie Brand Video Wood Mackenzie Values 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 Purpose: The Senior Analytics Engineer plays a critical role in advancing the organisation's analytics capability by designing, scaling, and governing high‑quality analytics-ready data assets on the Snowflake data platform using dbt (data build tool). This role operates with a high degree of autonomy and is recognised as a technical specialist within analytics engineering, acting as a key bridge between data engineering, data analysis, and business stakeholders. In addition to hands-on delivery, the Senior Analytics Engineer provides technical leadership, shapes best practices, and enables others through mentoring, guidance, and standards. The role has a strong focus on driving data quality, consistency, and scalability across domains, ensuring analytics outputs are trusted, performant, and aligned with business outcomes.

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