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.
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Job Description: Analytics Engineer
Role Purpose
A new Analytics Engineer position is being created to enhance the data team's capabilities in managing and transforming data within the Snowflake data platform using dbt (data build tool). This role will be pivotal in building a scalable and reliable data infrastructure to support analytics and data-driven decision-making across the business.
The Analytics Engineer will act as a bridge between data engineers and data analysts, applying software engineering best practices to the analytics workflow. This includes developing, testing, and deploying data models, as well as ensuring data quality and creating robust documentation.
Key Responsibilities:
The successful candidate will be responsible for:
Data Modelling and Transformation: Designing, developing, and maintaining scalable and efficient data models and transformation pipelines in Snowflake using dbt.
Workflow Management: Building and managing data transformation workflows, ensuring data is timely, accurate, and ready for analysis.
Data Quality and Governance: Implementing data quality tests and documentation to ensure the reliability and trustworthiness of the data. This includes supporting data governance and quality assurance activities.
Collaboration: Working closely with data analysts, data engineers, and business stakeholders to understand data requirements and deliver actionable insights. The role involves engaging directly with stakeholders and building their confidence in data-driven outcomes.
System Optimisation: Identifying opportunities to improve data processes, optimise performance, and ensure the scalability of the data platform.
Technical Expertise: Acting as a subject matter expert on dbt and Snowflake, providing guidance and best practices to the wider data team.
#LI-HH1
Candidate Profile:
The ideal candidate will possess a strong technical background combined with excellent analytical and communication skills.
Essential Experience and Qualifications:
A Bachelor’s degree in a quantitative field such as Data Science, Computer Science, or a related discipline.
2-4 years of hands-on experience in a data-focused role, with proven experience in data modeling and transformation.
Advanced proficiency in SQL for complex querying and data manipulation.
Demonstrable experience with dbt and cloud data warehouses, particularly Snowflake.
Proficiency with GitHub and AWS tools such as Step Functions, Athena, and S3, etc.
Strong discipline in attention to detail, data accuracy, and structured working practices.
Reliable execution and ownership of deliverables.
Proactive learner with genuine curiosity for emerging technologies and a commitment to continuous professional development.
Desirable Skills:
Proficiency in Python for data handling and automation.
Experience with ETL processes and data integration via APIs.
Familiarity with data visualization tools such as Power BI or Tableau.
A strong understanding of data governance frameworks and data security protocols.
Exceptional problem-solving skills and a high level of attention to detail.
The ability to translate complex technical concepts for non-technical audiences.
A collaborative spirit and a commitment to continuous professional development.
This new role is a fantastic opportunity for a data professional passionate about building modern data stacks and enabling organisations to leverage their data assets effectively.
Equal Opportunities
We are an equal opportunities employer. This means we are committed to recruiting the best people regardless of their race, colour, religion, age, sex, national origin, disability or protected veteran status. You can find out more about your rights under the law at www.eeoc.gov
If you are applying for a role and have a physical or mental disability, we will support you with your application or through the hiring process.