Associate Data Analyst

Why this role exists: The Associate Data Analyst is responsible for collaborating with stakeholders within a business unit to provide analytics, reporting, and insights that support growth objectives. This position plays a critical role in translating data from various digital and data systems, including the Officeworks Data and Analytics Platform, website, and app, into actionable performance-optimizing opportunities. By combining a strong analytical mindset with a strategic approach to problem-solving, the Associate Data Analyst ensures that complex insights are communicated effectively to drive data-driven decision-making across the enterprise.

Where you will make a difference: In this role you will: Analytics & Insights Delivery: Analyze business performance, customer behaviors, operational activity or functional data to identify trends, drivers, risks and opportunities. Clean, validate and reconcile data to ensure analysis is accurate, reliable and fit for purpose. Apply analytical techniques such as trend analysis, variance analysis, segmentation and hypothesis testing to answer business questions.

Turn complex data into clear insights, recommendations and decision support. Define and track metrics that help teams understand performance and measure outcomes. Communicate insights clearly to both technical and non-technical stakeholders.

Squad and Enterprise Initiative Support: Support squads, projects and enterprise initiatives by providing analysis, metrics, evidence and reporting to guide decisions. Work with Analytics Business Partners, Business Analysis & Process Improvement roles and business stakeholders to understand the business context behind each initiative. Help clarify what needs to be measured, what data is required and how success will be tracked.

Provide diagnostic analysis to support problem shaping, root-cause analysis and opportunity sizing. Support delivery teams by monitoring performance, identifying risks or trends, and providing insight throughout delivery. Contribute to benefits tracking by measuring whether delivered outcomes are being used and creating value.

Decision Support and Business Impact: Work with stakeholders to understand decision needs, performance questions and business priorities. Identify where analysis can improve decisions, reduce manual effort or improve business performance. Help teams interpret dashboards, reports and analytical outputs so they can take practical action.

Provide evidence-based recommendations that support planning, performance reviews, operational decisions and improvement activity. Highlight patterns, exceptions and emerging issues that may require business action. Reporting and Self-service Enablement: Develop, maintain or support dashboards and reporting outputs where required, with a focus on insight, measures and decision support.

Support effective use of trusted dashboards, reports and self-service tools. Help define business measures, reporting logic, data definitions and success metrics. Identify reporting gaps, inconsistencies, duplication or manual effort and recommend improvements.

Work with BI Developers and Analytics Engineers to ensure reporting and analytical outputs are accurate, useful and fit for purpose. Encourage use of approved data sources, consistent definitions and governed self-service pathways. Process & Continuous Improvement: Improve the quality, consistency and reusability of analysis, metrics and reporting outputs.

Identify opportunities to simplify recurring analysis, automate manual tasks and improve speed to insight. Document analysis assumptions, methodology, logic and limitations so outputs are transparent and reusable. Share analytical knowledge, techniques and business context with team members to build capability.

Proactively identify roadblocks, data issues or delivery risks and work with the right teams to resolve them. Governance, Standards and Responsible Use: Promote the use of trusted data sources, approved tools and consistent definitions. Handle sensitive data in line with Officeworks privacy, security and ethical standards.

Help business teams understand when work should be handled through self-service and when it should be escalated for specialist support. Encourage responsible and ethical use of data, analytics and AI-enabled insights. Who you will be working with: Internal Delivery Teams: Data Scientists, PowerBI Developers, AI/ML Engineers.

Internal Partners: Various business functions across Officeworks and technology functions. External Partners: Digital and Analytics agencies as required. What success looks like: Data-Driven Decisions: Business stakeholders successfully utilize provided reports and insights to enhance decision-making.

Project Delivery: Cross-functional projects are led effectively, with requirements and timelines coordinated to meet business needs. Self-Service Maturity: Improved self-serve environment allowing stakeholders to access fit-for-purpose actionable insights. Strategic Growth: Actionable recommendations directly contribute to driving business growth and achieving strategic goals.

How you will lead: Individual Contributor: Lives our Officeworks values and behaviors Proactively contributes to a safe working environment, escalates appropriately if there are unsafe conditions or inappropriate behaviour Operates in line with applicable Officeworks company policies and Code of Conduct Demonstrates a strong sense of personal accountability and curiosity to learn and develop Qualifications and work experience: Essential: Education: Bachelors degree in Commerce, Marketing, Business Analytics, Economics, Maths, Stats, or a related field. Minimum 4+ years of experience working in a similar analytics role partnering with stakeholders. MS Excel and/or data analytics and manipulation experience.

Experience with dashboard and reporting tools e.g. PowerBI, Tableau and similar reporting tools. Experience in querying large datasets with SQL.

Testing Experience: Experience with A/B and multivariate testing tools (e.g., Adobe Target, Optimizely, or Google Optimize). Preferred: Experience with A/B and multivariate testing tools, e.g., Adobe Target, Visual Website Optimizer, Optimizely, or Google Optimize (desirable). Retail Knowledge: Sound knowledge of retail industry dynamics and/or consumer behaviour.

Tool Familiarity: Valued experience with tools like Adobe Analytics, Google Analytics, Medallia, or Salesforce.