Job Description
Kogan.com is a pioneer of Australian eCommerce, and the software we build is used by millions of customers every day. You'll join a quick-moving engineering team with real ownership, shipping to production daily and using AI as part of how we work.
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As a Data Engineer you'll design and run the data and ML pipelines that let teams across Marketing, Purchasing, Logistics and Finance make confident, data-driven decisions.
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What you'll do:
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Scalable Pipeline Development: Design and maintain ETL/ELT pipelines capable of handling 10M+ daily events and large-scale data transfers across our platforms.
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Data Modeling: Develop and optimize data models in environments like BigQuery or Snowflake to ensure high performance for both analytics and ML training sets with optimal cost
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Support ML Workflows: Build the underlying features and data inputs required for Machine Learning models
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Develop and refine ML models for practical business use cases, such as customer sentiment, churn prediction or demand forecasting
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MLOps Integration: Establish and maintain MLOps pipelines to help automate the deployment and monitoring of models in production.
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System Integration: Work with internal APIs and third-party tools to ingest data efficiently while maintaining strict data integrity.
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Governance & Quality: Implement best practices for data quality, security, and documentation to ensure our data remains a "source of truth."
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Development according to software engineering best practices (Git, CI/CD, trunk based development, tests)
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AI Collaboration:



Contribute to experiments with AI and LLMs to assess how they can be practically applied to solve business problems.
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What you'll need:
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Strong SQL Foundations: Solid experience writing and optimizing SQL for commercial-scale products (e.g., handling millions of rows and complex joins efficiently).
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Pipeline Orchestration: Proven experience using tools like Airflow, dbt, or AWS Glue to manage and monitor production-grade data workflows.
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Python Proficiency: Strong Python skills for data transformation, scripting and interacting with various data sources.
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ML Engineering Exposure: Practical experience building the data infrastructure that supports machine learning, including data preprocessing and model deployment pipelines. Experience with machine learning models development
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Cloud Experience: Hands-on experience with cloud data platforms, with a strong preference for GCP.
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Software Best Practices: Familiarity with Git, CI/CD, and basic containerization (Docker) to ensure code quality and deployment reliability.
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Problem-Solving Mindset: A practical approach to engineering that balances the need for speed with long-term system stability.
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Bonus Points
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Experience with event streaming (e.g., Kafka, Kinesis) for real-time data needs.
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Exposure to ML platforms and tools such as SageMaker, Vertex AI, or Databricks.
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Familiarity with BI and visualization tools like Looker or Tableau.
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An interest in eCommerce dynamics and customer behavior analytics.
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Why Kogan.com?
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Our culture is unlike anywhere else and regardless of where you are in your career journey, we empower you to do your best work and have a big impact. Check us out
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Work with an incredible team to solve important challenges, helping to drive Australia and New Zealand's eCommerce future
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Your role has a lot of ownership, autonomy and little red tape. You'll be empowered to achieve positive outcomes and your work will have a real impact
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You'll be at the forefront of the eCommerce industry and be part of a company that are the Pioneers of eCommerce in Australia
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Be an Intrepreneur, playing a hands on role in shaping our strategy at our HQ
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Learning budget of $****
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A range of employee benefits such as; complimentary Kogan First Membership, team exclusive discounts, Health & Wellness program, Learning & Development and Lunch & Learns, Hackathons, Team member referral program, Company and team events and celebrations, community engagement (volunteering) and extensive career development opportunities plus loads more!
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To find out more about how we work, our tech stack, processes and company culture, visit

and

#J-*****-Ljbffr

📌 Data Engineer (Melbourne)
🏢 Kogan.com
📍 Melbourne