QA Associate Analyst

Why this role exists:

The QA Associate Analyst ensures the reliability, accuracy, and trustworthiness of Officeworks' data, analytics, and AI solutions. This role plans, tests and validates complex data flows, reporting, analytics and AI decision logic to ensure every output is compliant, explainable, and aligned with business rules. This will include testing for alignment to functional and non-functional requirements.

Where you will make a difference:

In this role you will:

End-to-End Data & AI Validation

• Plan and deliver end to end QA activities for data, analytics, and AI solutions, including test planning and design.
• Validate data flows from source systems through transformation to analytics, reporting, and AI driven consumption.
• Test AI and machine learning solutions to ensure outcomes are trustworthy, explainable, and compliant.
• Identify and mitigate risks related to accuracy, bias, drift, and changes in data or models.
• Validate AI decision logic, ensuring that automated outcomes remain aligned with established business rules.

Technical Testing & Automation

• Validate ETL/ELT processes and APIs, ensuring seamless integration between platforms like Snowflake and SAP Datasphere.
• Design and maintain automated data validation tests to ensure efficient regression coverage and reliability.
• Validate analytical outputs, confirming that reporting remains accurate as the business democratises data access.
• Validate non functional requirements specifically for data intensive and AI enabled solutions.
• Apply technical adaptability to perform data-related tasks that support broader team objectives and architectural transitions.

Collaboration & Continuous Improvement

• Support UAT and releases, collaborating with data engineers, product owners, and business stakeholders.
• Strengthen QA practices through continuous improvement, identifying high-value processes to enhance system efficiency.
• Maintain structured documentation of technical logic and testing protocols to ensure long-term system sustainability.
• Work closely with multi-disciplinary squads to align testing efforts with the rapid pace of AI and data development.

Who you will be working with:

• Data & AI Hub: Working with AI Technology Associate Manager, Engineers, and Data Modellers to validate new features.
• Leadership: Partnering with functional leads to ensure delivery meets corporate quality standards.
• Data Science Capability: Aligning testing protocols with the broader data science team.
• Cross-functional Stakeholders: Engaging with Product Owners and Business Leads to support User Acceptance Testing (UAT).

What success looks like:

• Outcome Trustworthiness: AI and ML solutions are consistently validated for accuracy, effectively preventing bias or drift in production.
• Data Integrity: Reliable data flows across all platforms (Snowflake/Datasphere), ensuring a "single source of truth" for the business.
• Efficiency: Automated validation suites reduce manual testing effort and increase the speed of high-quality releases.
• Standards Compliance: All analytical and AI outputs are rigorously tested against business rules and non-functional requirements.

How you will lead:

Individual Contributor

• Lives our Officeworks values and behaviours
• 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 Computer Science, Information Technology, or a related field.
• Experience: 5+ years of experience in QA or Data Analyst roles, with a focus on data-centric testing and analytics.
• Technical Mastery: Essential knowledge of GitHub, Snowflake, and machine learning (ML) systems.
• Adaptability: Demonstrated ability to understand the transition from traditional data testing to AI and model-based validation.
• QA Expertise: Proven experience in validating ETL/ELT, APIs, and non-functional requirements for large-scale systems.
• Cultural Fit: A proactive problem-solver who values deep technical experience and practical application.

Preferred

• Automation Skills: Experience in designing and maintaining automated reconciliation and validation tests.
• Retail Context: Familiarity with high-volume omnichannel retail environments and modern cloud data migrations.