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 worlds most influential energy producers utilities companies financial institutions and governments.
Now with the worlds energy system more complex and interconnected than ever before sector-specific views are no longer enough. Thats why weve redefined whats 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 2700 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
Wood Mackenzie Values
Overview
We are seeking a highly motivated Data Analyst to support our expanding Lower 48 oil and gas research and analytics team. The ideal candidate has hands-on experience working with large complex well-level datasets strong technical skills in PySpark Python and cloud technologies (AWS preferred) and a passion for building scalable reliable data solutions. This role involves data pipeline development ETL processing data quality assurance and direct support for analysts and researchers.
Design develop and maintain data pipelines using PySpark Python and cloud-native tools.
Build and optimize ETL processes for ingesting transforming and validating large oil and gas datasets.
Integrate data from cloud environments into unified models.
Perform data discovery cleansing validation and anomaly detection.
Conduct thorough quality assurance across multiple datasets (production completions costs well attributes etc.).
Create and maintain data flow diagrams source-to-target mappings and documentation.
Reverse-engineer existing scripts workflows and legacy logic to understand data lineage and implement improved solutions.
Collaborate closely with the research and analytics teams to understand data needs and provide timely insights.
Drive automation and process optimization including leveraging AI tools and frameworks to improve analyst workflows.
Produce comprehensive technical and functional documentation including SOPs design specs and system overviews.
Work with cross-functional teams using tools such as Jira Confluence TFS Excel PowerPoint and Visio.
Experience in data analysis data engineering or data development.
Strong programming skills in PySpark and Python.
Experience with AWS or other cloud platforms for data development and integration.
Ability to work with large complex datasets and develop scalable data solutions.
Strong analytical troubleshooting and problem-solving skills.
Excellent verbal and written communication skills including documentation.
Experience working with Lower 48 oil & gas or broader energy industry datasets (production completions well records cost data etc.).
Experience working across hybrid environments (cloud on-prem).
Familiarity with data orchestration tools version control and CI/CD workflows.
Ability to analyze or enhance legacy code by reverse-engineering logic and improving performance.
Demonstrated ability or willingness to incorporate AI-driven tools into daily workflows.
Detail-oriented with a strong sense of ownership and accountability.
Comfortable working in a fast-paced research-driven environment.
Flexible collaborative and able to communicate complex technical topics clearly.
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.
Required Experience:
IC
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