Data Associate

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.

**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**

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 Data Associate (with Maintenance and Support experience) 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 to deliver the Product.

**Key Responsibilities**:
**Application Maintenance**:

- Identify and escalate issues and document resolutions for faster troubleshooting.

**Operationalization**:

- Work closely with cross-functional teams to operationalize systems, ensuring seamless integration into the production environment.
- Develop and implement procedures for efficient system operation and maintenance.

**Daily Jobs Monitoring**:

- Monitor and manage daily batch jobs and data loads (including daily, weekly, and quarterly schedules), promptly addressing issues related to job failures, delays, or deviations from expected outcomes.
- Ensure the successful completion and validation of data loads across multiple frequencies, maintaining data accuracy and integrity.
- Implement proactive measures to anticipate and prevent potential operational challenges.
- Prepare daily/weekly status reports on job execution and highlight anomalies for quick resolution.

**User Support - Data Extracts and Analysis**:

- Assist users in extracting bespoke data sets, providing guidance on data formats, and ensuring data integrity.
- Collaborate with users to understand their analysis requirements and provide support in utilizing tools for effective data analysis.
- Work on ad-hoc data requests and maintain a repository of commonly used queries/reports for reuse.

**Incident Response**:

- Diagnose and troubleshoot technical issues related to data extraction and analysis, collaborating with teams to implement corrective actions
- Log incidents systematically, track progress, and ensure timely closure with effective coordination.

**Collaboration & BAU Support**
- 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.
- Act as first-level support to reduce dependency on other team members for routine issues.

**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.

**Automation**:

- 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

**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.

**Continuous Improvement**
- Actively identify inefficiencies, bottlenecks, or pain points in current processes and propose actionable solutions.
- Share innovative ideas and collaborate with team members to imple