Senior Data Analyst - Subsurface

In the middle of the energy transition, businesses and governments are faced with significant challenges. But the pace and scale of change mean every decision is made under mounting pressure. Now, more than ever, companies need reliable data, analytics and actionable insight.

Wood Mackenzie is the leading global provider of data and analytics solutions for the renewables, energy and natural resources sectors.

Wood Mackenzie’s services include data, analytics, insight, events and consultancy. A trusted partner for over 50 years, Wood Mackenzie’s team has over 2,300 experts across more than 30 global locations who cover the entire supply chain.

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

Job Description

Our expertise in upstream oil and gas and energy transition is driven by our unique databases, products, economic models and forecasts. The ambition of the Subsurface Data group is to drive new commercial insight and analysis from Subsurface Oil and Gas data. In order successfully achieve this, the team will require a fundamental understanding data pipelines and subject domain expertise in Geology/Petroleum Engineering. This will include the definition of core data models, the ability to perform large and complex queries across oil and gas datasets and produce sophisticated visualisations. The group will drive the subsurface data quality agenda through prioritisation, measurements and coordinated improvements throughout the data lifecycle.

Role propose

Research and analyse regional geology of the area

Process various types of Subsurface oil and gas data, including basins, plays, prospects, field reservoirs, saline aquifers and well formation tops/tests/targets

Act as the Subsurface oil and gas data owner, understanding the commercial implications within a specific domain and data platform. Responsible for sourcing, maintaining, ensuring quality, and controlling data for the respective domain coverage area

Understand database structure and ensure best practices are applied to utilise or maintain databases, tools, models and processes solutions from data sourcing to customer delivery

Implement quality control measures on our dataset to ensure data consistency and integrity

Lead high-priority projects and initiatives aimed at improving data quality or processes, ensuring alignment with the broader data vision

Collaborate with junior colleagues, providing training, monitoring adherence to best practices, and ensuring accurate completion of tasks

Work in an agile, collaborative manner to foster an environment of continuous improvement and incremental delivery

Develop relationships with key stakeholders across the wider Data team, including Data Engineers, Product, Research, and Sales

Qualifications

Bachelor and Master's degree in Petroleum Engineering or Geology or equivalent experience

Work experience in a similar position

Fluent in SQL

Experience in at least one popular programming language (ideally Python)

Experience working with data visualization tools (Spotfire, Power BI)

Understanding of the theory of DBMS and ETL processes

Experience working with databases and ArcGIS is a plus

Keen interest in applied mathematics, data science, and engineering

Strong communication skills – particularly the ability to work in a сross regional team and interact with colleagues and external contacts in multiple geographic locations

English (advanced spoken and written)

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

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.

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