Available Jobs at Woolworths

Introduction

• In this role, you will be responsible for developing a range of Kids Footwear that is customer-focused, trend-relevant, and profitable.
• Ensuring that the product strategy is aligned to the company’s brand positioning and seasonal objectives.
• You will take ownership of the product journey from concept & design, developing product, briefing suppliers and working with footwear technologists to execute Quality product and a balanced assortment.

Job description

• The development and execution of the seasonal departmental strategy that delivers against key customer, brand, and commercial objectives.
• Collaborate with Head of Buying, Design and Sourcing to define the product and trading strategy in line with agreed KPIs.
• Leverage global and local insights and include trend forecasting, post-seasonal analysis, customer analytics, and competitive benchmarking (e.g. EDITED, First Insights) to inform product direction.
• Present seasonal product workshops and range assortment recommendations, including must-win categories and channel-specific needs.
• Procure a balanced product range across Core, Key & Fashion items, that is Customer Centric, Quality driven with a clear pricing architecture.
• Collaborate with Sourcing and TPD to develop and approve products, manage sample sign-off, and ensure critical path and merchandise cycle milestones are met.
• Conduct product reviews and final range presentations, incorporating display and packaging strategies to enhance in-store execution.
• Weekly analysis of trade using performance reports, to inform decisions, drive actions and optimize sales.
• Actively contribute to weekly trade reviews and align actions with your team (Quad, Marketing, Visual Merchandising, and Supply Chain).
• Keep the customer at the heart of your decision making by using customer insights, reviews, and research to shape product and range choices.
• Contribute to competitor intelligence through regular market research, store visits, and supplier feedback.
• Support promotional planning and recommend markdowns and volume adjustments based on performance.

Minimum requirements

• Relevant tertiary qualification in Fashion, Retail Buying, or Commerce.
• 2–3 years’ experience in Footwear Buying
• A strong understanding of a Kids Footwear Business.
• Strong computer literacy, with proficiency in Excel, PowerPoint, PLM, and EDITED.
• A passion for Quality Footwear.
• A continuous learning mindset with a drive for personal and professional growth.
• Solid understanding of retail business and buying processes, including critical path management.
• Up-to-date knowledge of the retail market and industry landscape.
• Strong grasp of pricing strategies including markdowns, markups, sell-through, and visibility drivers.
• Excellent numerical and analytical skills, with the ability to interpret data and drive product decisions.

Apply by: 30 June 2025

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Introduction

• To achieve the team’s goals by providing administrative support to the Buyer to ensure the smooth running of the department.

Job description

• Assist in ensuring the product range is delivered timeously to meet our customers’ needs 
• Provide input into the development and delivery of the departmental strategy. 
• Ensure garments are available for all reviews.  
• Management of Critical Path via RMS / PLM. 
• Contract and purchase order management.  
• Ensure that all red and black seals are approved.  
• Administer all contract and import orders. 
• Administer and maintain RMS, including item set up, preparation and management of contracting and management of buying ordering process.  
• Manage the control of review and marketing samples as well as sample sales. 
• Ensure that the venue and relevant documents are prepared for reviews. 
• Liaise with stores, franchisees and suppliers. 

Minimum requirements

• Relevant qualification (i.e. Design, Clothing and Retail Management). 
• Administrative experience in a retail environment preferable or experience in a clothing manufacturing environment. 
• Previous buying environment experience (advantageous)
• Demonstrated taste level and flair 
• Customer orientation 
• Team player 
• Effective communication skills 
• Planning and organizing ability 
• Strong administrative skills 
• Results driven and proactive 
• Attention to detail 
• Ability to work under pressure 
• Computer literacy 

Apply by: 11 July 2025

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Introduction

• The Engineering Manager: AI/ML is responsible for leading and scaling the machine learning engineering function within the organisation.
• This role focuses on the development, deployment, and operationalisation of ML models, ensuring they are robust, scalable, and effectively integrated into business processes.
• Working closely with Data Science, Data Engineering, Platform and Cloud Architecture teams, the Engineering Manager: AI/ML ensures that ML initiatives drive value while adhering to best practices in MLOps, model governance, and performance optimisation.
• This position combines technical expertise, strategic vision, and leadership to develop a high-performing ML engineering team and deliver impactful AI solutions.

Job description

• Work closely with MLOps Engineers in the Platform team to ensure adherence to established MLOps policies and frameworks.
• Lead the end-to-end deployment of machine learning models, ensuring reliability, scalability, and business impact.
• Ensure seamless integration of ML models into production systems and data pipelines.
• Work collaboratively with Data Science team to translate research prototypes into production-grade solutions.
• Implement governance frameworks for model performance tracking, versioning, and continuous learning.
• Build and manage a high-performing ML Engineering team, fostering a culture of innovation and excellence.
• Champion the use of cloud-based ML infrastructure (AWS SageMaker, Databricks, Kubernetes, etc.) for scalable deployment.
• Optimize model inference pipelines, ensuring they are efficient and cost-effective in production environments.
• Develop strategic partnerships with business units to align AI/ML initiatives with company objectives.
• Maintain compliance with ethical AI principles, security, and data privacy in all ML-driven applications.

Minimum requirements

• Master's or Bachelor's degree in Computer Science, Data Science, Artificial Intelligence, or related fields.
• Minimum 6 years in machine learning engineering, with at least 2 years in a leadership role.
• Strong experience in MLOps, CI/CD for ML models, and cloud-based AI solutions.
• Proficiency in Python, TensorFlow, PyTorch, and MLflow.
• Expertise in cloud ML services (AWS SageMaker, Azure ML).
• Experience with containerisation and orchestration (Docker, Kubernetes).
• Strong background in ML model optimisation, inference serving, and monitoring.
• Understanding of data engineering workflows, feature engineering, and model deployment pipelines.
• Ability to lead and mentor ML engineers and collaborate with cross-functional teams.
• Strong stakeholder management, bridging the gap between business and technical teams.
• Excellent problem-solving skills and ability to drive AI adoption across the organisation.

ADDITIONAL CRITERIA

• Strategic Thinking: Ability to align ML initiatives with broader business goals.
• Collaboration & Communication: Works effectively across data science, engineering, and business teams.
• Innovation-Driven: Keeps up with emerging trends in AI/ML, experimenting with new techniques and technologies.
• Problem-Solving: Proactively identifies bottlenecks in ML pipelines and ensures continuous improvements.
• Adaptability: Thrives in a fast-paced AI-driven environment, adjusting strategies as needed.
• Cultural Fit: Demonstrates integrity, accountability, and a commitment to fostering a high-impact AI/ML team.

Apply by: 4 July 2025

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Introduction

• Data Engineer who will assist in designing and implementing scalable and robust processes to support the data engineering capability.
• This role will be responsible for extracting and transforming massive amounts of data at scale and consolidating this data into a bigger data ecosystem.

Job description

• Design, build, and maintain scalable, automated data pipelines using AWS services like Glue, Lambda, Step Functions, EMR, and Kinesis.
• Develop ETL/ELT processes to ingest, transform, and deliver structured and unstructured data into data lakes, data warehouses, and analytical environments.
• Ensure efficient batch and real-time data processing, optimising workflows for performance, scalability, and cost efficiency.
• Implement robust data movement strategies, ensuring secure and efficient data transfer across cloud storage layers.
• Develop and maintain data transformation logic, ensuring data is structured for engineering, AI/ML, and analytics use cases.
• Implement change data capture (CDC) mechanisms to support real-time data synchronisation and streaming analytics.
• Optimise large-scale data processing workflows for performance and efficiency.
• Ensure data pipelines feed into AWS-based data lakes (S3), data warehouses (Redshift), and feature stores for AI/ML.
• Enable AI/ML and analytics teams with structured, high-quality data, ensuring seamless integration with their models and insights.
• Collaborate with engineering teams to support automated, self-service data access.
• Develop CI/CD pipelines to automate testing, deployment, and monitoring of data workflows.
• Leverage Infrastructure as Code (IaC) tools like Terraform and CloudFormation for scalable cloud data infrastructure automation.
• Implement version control, rollback strategies, and automated alerting for pipeline reliability.
• Continuously optimise data pipelines to improve performance, reduce latency, and minimise operational costs.
• Stay up to date with advancements in cloud-based data engineering and best practices.

Minimum requirements

• Bachelor’s degree in Computer Science, Business Informatics, Mathematics, Statistics, or Engineering.
• 4 - 5 years of relevant data engineering experience in cloud-based environments.
• AWS Certifications (AWS Data Analytics, AWS Solutions Architect) are advantageous.
• Strong understanding of data structures, algorithms, and software design applied to cloud-based data engineering.
• Experience working with structured and unstructured data at scale, including key-value, document, and columnar data stores.
• Proven expertise in AWS services, including Redshift, Glue, Lambda, EMR, S3, IAM, RDS, and Athena.
• Experience building and optimising cloud-based ETL/ELT pipelines for analytics, reporting, and AI/ML workloads.
• Strong programming, performance tuning, and troubleshooting skills using Python, Scala, Java, and C .
• Hands-on experience with distributed data processing frameworks, including Apache Spark and AWS Glue.
• Experience designing and implementing AWS-based data solutions, including data lakes, event-driven architectures, and API integrations.
• Experience working with streaming data solutions, including Kafka, Kinesis, and change data capture (CDC) synchronisation.
• Proficiency with DevOps-oriented data engineering, including CI/CD automation and Infrastructure as Code (Terraform, CloudFormation).
• Experience with version control systems, including Git and SVN.
• Expertise in monitoring and troubleshooting data pipelines using AWS CloudWatch.

ADDITIONAL CRITERIA

• Analytical Mindset: Demonstrates a strong analytical and problem-solving ability, capable of breaking down complex data issues and devising effective solutions.
• Collaboration and Communication: Exhibits excellent interpersonal and communication skills, with the ability to articulate complex data concepts to non-technical stakeholders. Must foster a collaborative team environment and efficiently work across different departments.
• Continuous Learning: Has a strong commitment to continuous professional development, staying ahead of the latest trends and technologies in data engineering and analytics.
• Willingness to pursue relevant certifications and training.
• Innovative Thinking: Displays innovative thinking and a proactive approach to identifying and pursuing opportunities to improve data processes and solutions. Comfortable proposing and experimenting with new technologies or methodologies to enhance data capabilities.
• Adaptability: Demonstrates flexibility in adapting to changing business needs and technology landscapes.
• Can efficiently manage multiple priorities and adapt strategies in a fast-paced environment.
• Cultural Fit: Aligns with the organisation's culture and values, contributing positively to team dynamics and company morale.
• Demonstrates integrity, accountability, and a strong work ethic.

Apply by: 3 July 2025

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Introduction

• The AI/ML Engineer will be responsible for operationalizing AI/ML models developed by the Data Science team, ensuring their seamless integration into production environments.
• This role focuses on deploying, monitoring, and maintaining AI/ML models, optimising system performance, and automating MLOps processes to enhance scalability and reliability.

Job description

• Deploy and operationalize AI/ML models developed by the Data Science team into scalable production environments.
• Develop and maintain robust machine learning pipelines to enable efficient model inference and data transformation.
• Ensure seamless integration of AI/ML models with enterprise applications and data systems.
• Implement MLOps best practices, including CI/CD for machine learning, model versioning, monitoring, and automated retraining.
• Optimize AI/ML workflows for performance, cost efficiency, and resilience.
• Collaborate with data engineers to ensure data pipelines support AI/ML model inference and training.
• Leverage cloud-based AI/ML services (AWS SageMaker, Lambda, Glue, etc.) to streamline model deployment and automation.
• Implement AI-driven monitoring and alerting mechanisms to detect model drift and performance degradation.
• Work closely with business stakeholders to ensure AI/ML models are delivering expected value.
• Ensure AI/ML solutions adhere to best practices for security, compliance, and governance.
• Provide technical support and troubleshoot AI/ML model issues in production environments.

Minimum requirements

• Bachelor’s degree in computer science, Engineering, or a related field with 4 - 5 years of experience in operationalising AI/ML models in production environments.
• Strong understanding of AI/ML deployment strategies, including containerization, orchestration, and inference optimisation.
• Experience with implementing MLOps principles, including CI/CD pipelines, automated model monitoring, and retraining.
• Proficiency in Python, with experience in AI/ML frameworks such as TensorFlow, PyTorch, or Scikit-learn.
• Expertise in data engineering tools and frameworks such as Apache Spark, AWS Glue, and SQL.
• Practical experience with AWS services, including SageMaker, Lambda, S3, IAM, and RDS.
• Experience working with structured and unstructured data within enterprise environments.
• Strong software development skills, with experience in version control systems such as Git.
• Familiarity with containerisation and orchestration tools (Docker, Kubernetes) for AI/ML workloads.
• Knowledge of cloud security, data governance, and compliance considerations.
• Excellent verbal and written communication skills; must work well in an agile, collaborative team environment.

ADDITIONAL CRITERIA

• Analytical Mindset: Strong problem-solving ability to optimise AI/ML deployment and system performance.
• Collaboration and Communication: Ability to work closely with data scientists, data engineers, and business stakeholders to ensure seamless AI/ML integration.
• Continuous Learning: Commitment to staying updated on the latest MLOps trends, tools, and automation techniques.
• Innovative Thinking: Proactive in identifying and implementing AI-driven automation and model optimisation improvements.
• Adaptability: Ability to manage multiple AI/ML model deployments and adapt strategies in a fast-paced environment.
• Cultural Fit: Aligns with the organisation’s values, demonstrating integrity, accountability, and a strong work ethic.

Apply by: 3 July 2025