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.