Data Associate

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

Responsibilities

Knowledge

• Performs defined tactical tasks with clear guidance to manage data effectively.
• Clarifies outcomes, goals, and hypotheses to ensure alignment with objectives.
• Demonstrates foundational skills in core data practices, including:
• Visualisation techniques for exploratory data analysis (with assistance).
• Scripting language proficiency and data-gathering methods.
• SQL querying to retrieve and manipulate data.
• Tackles defined problems, seeks feedback, clarifies approaches, and delivers solutions.
• Maintains a growth mindset, continually developing technical and analytical skills.
  

Impact

• Meets clear expectations for quality and timely delivery of tasks.
• Develops core skills to interpret data from diverse sources using SQL, Excel, or Python.
• Builds effective working relationships with peers and stakeholders.
• Actively participates in learning and development opportunities, demonstrating a commitment to growth.
• Proactively seeks feedback, speaks up in meetings, and experiments with new techniques.
  

Collaboration

• Works closely with data teams to ensure accurate task completion.
• Supports data governance and quality assurance initiatives.
• Collaborates with Research, Product, Data Owners, Data Engineering, and core business functions.
• Maps stakeholders, dependencies, and communication channels clearly.
• Contributes to fostering a rich culture of inclusion and diversity within the team.
  

Innovation

• Identifies opportunities to improve workflows using personal skills or team resources.
• Continuously improves technical skills and seeks feedback to enhance expertise.
  

Specialisms

• Problem Solving: Develops structured approaches to solving defined problems.
• Data Handling and Analysis: Gains proficiency in managing, cleaning, and analysing datasets.
  

Key Expectations

Experience & Qualifications

• Bachelor’s degree in a relevant field or equivalent experience.
• Basic understanding of data analysis principles and workflows.
• Foundational proficiency in SQL and at least one scripting language (e.g., Python).
• Familiarity with visualisation tools or techniques for exploratory data analysis.
• Familiarity with Snowflake advantageous.
  

Technical Skills

• Ability to perform basic data manipulation and querying.
• Exposure to data governance and quality assurance activities is a plus.
• Interest in developing skills in ETL processes and database management.
  

Soft Skills

• Detail-oriented with a proactive approach to seeking feedback and assistance.
• Strong communication skills, eager to collaborate across teams.
• Enthusiastic about learning and contributing to team goals.
  

Equal Opportunities