Senior Data Analyst

Wood Mackenzie is the global data and analytics business for the renewables, energy, and natural resources industries. Enhanced by technology. Enriched by human intelligence. In an ever-changing world, companies and governments need reliable and actionable insight to lead the transition to a sustainable future. That’s why we cover the entire supply chain with unparalleled breadth and depth, backed by over 50 years’ experience. Our team of over 2,400 experts, operating across 30 global locations, are enabling customers’ decisions through real-time analytics, consultancy, events and thought leadership. Together, we deliver the insight they need to separate risk from opportunity and make confident decisions when it matters most.

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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

Do you have a passion for Data? Are you a Problem-Solver with an ability to quickly understand complex processes?  Then this role could be for you. We are looking for a Senior Data Analysis to join our Metals & Mining Data team.

This role will focus on the analysis, programmatic acquisition, and preparation of data for delivery to our customers and research teams.

We are looking for someone with a focus on ensuring end to end data processes and also set up BAU operations for our products.

The successful candidate for this role must have a strong Data background and understand the challenges of building a modern data centric business with a commitment to incremental delivery. Proven experience of data transformation projects, and the ability to articulate ideas effectively across all business areas is essential. 

Job Overview: Role Overview

We are seeking a highly experienced Senior Data Analyst to lead Business-As-Usual (BAU) data operations, ensuring the reliable and efficient delivery of critical data services. While BAU operations will be the core responsibility, the role will also involve data development tasks as needed to support continuous improvement efforts. This position requires strong technical expertise, deep analytical capability, and the ability to manage and optimize daily operational processes in a fast-paced environment. The ideal candidate will be the subject-matter expert for our data landscape, proactively drive improvements, and ensure reliable delivery of critical data services.

• 8–10 years of experience in data analysis, data engineering, data development and BAU roles.

• Experience leading BAU operations, including troubleshooting, process management, and continuous improvement.

• Strong background in data discovery, data cleansing, validation, data flow mapping, and source-to-target transformation.

• Hands-on experience building and maintaining data pipelines using SQL and Python; VBA knowledge is a plus.

• Ability to reverse-engineer existing scripts/code to understand logic and develop improved solutions.

• Experience working across cloud and on-premise environments (AWS preferred) for data integration and development.

• Deep understanding of data modeling, data warehousing, data lakes, and automated data ingestion processes.

• Experience with APIs, web scraping, and integrating external data sources.

• Skilled in developing reports, dashboards, KPIs, and communicating insights effectively.

• Proficient in tools such as Jira, Confluence, TFS, Excel, PowerPoint, and Visio.

• Excellent writing skills for producing technical and functional documentation.

• Experience in Metals & Mining or Energy industry is an advantage.

Key Responsibilities:

• Data Development & Engineering

• • Design, enhance, and maintain data pipelines using SQL and Python for ingestion, transformation, validation, and automation.

  • Reverse-engineer existing scripts and workflows to understand logic and rebuild optimized, scalable solutions.

  • Support the design and development of data models, data warehousing, and data lake structures, aligned with business needs.

  • Integrate internal and external data sources using APIs, web scraping, or other ETL methods.

  • Continuously improve the data landscape by evaluating and implementing new technologies, including Snowflake integration and other modern cloud-based solutions.

  • Ensure data accuracy and reliability through automated checks, profiling, and data quality frameworks.

• Data Analysis & Insights

• • Gain a deep understanding of customer data, business processes, and the broader data ecosystem—acting as the go-to expert for data-related queries.

  • Perform in-depth data exploration, cleansing, validation, and reconciliation to support analytics, reporting, and business decision-making.

  • Translate business requirements into clear, actionable technical specifications and analysis outputs.

  • Develop dashboards, KPIs, metrics, and reports to deliver actionable insights to stakeholders.

  • Communicate findings effectively to both technical and non-technical audiences.

• BAU Operations

• • Lead end-to-end BAU data operations, ensuring timely, reliable delivery of daily and periodic data processes.

  • Set up and refine operational workflows, documentation, monitoring, and SLAs for efficient data operations.

  • Troubleshoot data pipeline issues, data quality problems, and system errors; coordinate with engineering and business teams for timely resolution.

  • Manage prioritization, resource planning, and operational workload distribution across the team.

  • Continuously identify opportunities to automate manual tasks, streamline operations, and improve process efficiency.

  • Serve as an escalation point for urgent data-related incidents, ensuring minimal business disruption.

  • Work closely with the wider Data team, Data Engineering, Research, and Product teams to ensure smooth business-as-usual (BAU) operations.

  • Provide daily support and communication across functions to resolve issues, share updates, and align on priorities.

  • Foster strong partnerships with stakeholders to ensure data reliability, timely delivery, and continuous improvement of processes.

• Documentation:

• • Maintain accurate and up-to-date documentation for operational procedures, configurations, and user support processes.

  • Contribute to the development and enhancement of a comprehensive knowledge base.

  • Ensure all resolutions, queries, and new learnings are logged in documentation for team-wide benefit.

• AI Enablement

• • Explore opportunities to leverage AI and machine learning tools to enhance data quality, streamline extraction processes, and improve analysis capabilities.

  • Support the integration of AI-driven solutions into existing workflows, collaborating with data engineers and analysts to test, validate, and optimize models.

  • Stay informed on emerging AI tools relevant to data operations and provide recommendations for adoption.

  • Assist in preparing datasets for AI/ML initiatives and monitoring model outputs for accuracy.

• Automation & Continuous Improvement

• • Identify opportunities for automation to streamline operational tasks, data extraction processes, and improve efficiency.

  • Implement automation scripts or tools to simplify routine maintenance and monitoring activities

  • Actively identify inefficiencies, bottlenecks, or pain points in current processes and propose actionable solutions.

  • Share innovative ideas and collaborate with team members to implement process improvements that enhance productivity, data accuracy, and overall service quality.

  • Contribute to fostering a culture of continuous learning and improvement within the team

  • Participate in team retrospectives, contribute feedback, and implement improvement action items.

• Personal Attributes

• • Strong analytical mindset with a systematic and logical approach to problem-solving.

  • Highly collaborative, able to bridge the gap between technical and non-technical stakeholders.

  • Comfortable managing multiple priorities in a dynamic, fast-paced environment.

  • Detail-oriented with a focus on data accuracy and operational reliability.

  • Proactive, adaptable, and able to take ownership of both strategic and operational tasks.

  • Excellent problem-solving skills, with a proactive approach to identifying and resolving issues.

  • Clear communicator, providing timely updates, raising concerns, and suggesting solutions.

  • Demonstrates adaptability and responsiveness in a fast-evolving environment.

  • Builds strong working relationships and collaborates effectively across teams.

  • Willingness to handle routine operational tasks while growing into more advanced responsibilities.

Qualifications:

• Bachelor's or Master’s degree in Computer Science, Information Technology, or a related field.

Expectations

o   We are a hybrid working company and the successful applicant will be expected to be physically present in the office at least 2 days per week to foster and contribute to a collaborative environment, but this may be subject to change in the future.

o   The nature of this role precludes it from consideration for part-time, fully remote or flexible working arrangements

• Due to the global nature of the team, a degree of flexible working will be required to accommodate different time zones.

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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.