Data Engineer

About the Role

Kogan.com is a well-known Australian eCommerce business whose technology supports millions of customers every day. In this role, you will be part of a fast-paced engineering group that owns its work end-to-end, releases to production frequently, and uses AI as part of day-to-day delivery.

As a Data Engineer, you will build and operate data and machine learning pipelines that help teams in Marketing, Purchasing, Logistics, and Finance make reliable, data-led decisions.

What You Will Do

• Create and support scalable ETL and ELT pipelines that can process more than 10 million events each day and move large data volumes across internal platforms.
• Design, improve, and maintain data models in systems such as BigQuery or Snowflake, with attention to speed, analytics performance, machine learning training needs, and cost efficiency.
• Develop the supporting data features and inputs needed for machine learning initiatives.
• Build and refine machine learning models for practical business applications such as customer sentiment analysis, churn prediction, and demand forecasting.
• Set up and maintain MLOps workflows that automate model deployment and monitoring in production.
• Integrate with internal APIs and external tools to bring data in efficiently while protecting data accuracy and integrity.
• Apply strong data governance practices, including quality checks, security controls, and documentation so the data remains a trusted source of truth.
• Work in line with modern engineering practices such as Git, CI/CD, trunk-based development, and testing.
• Experiment with AI and large language models to evaluate how they can be used to solve business problems in practical ways.

What We Are Looking For

• Deep SQL experience, including writing and tuning queries for commercial systems with millions of rows and complex joins.
• Hands-on experience with workflow orchestration tools such as Airflow, dbt, or AWS Glue in production environments.
• Strong Python skills for data transformation, scripting, and working with varied data sources.
• Practical exposure to ML engineering, including data preparation and pipelines that support model deployment, along with experience developing machine learning models.
• Experience working with cloud-based data platforms, ideally with a preference for GCP.
• Comfort with engineering best practices such as Git, CI/CD, and basic Docker containerization.
• A pragmatic problem-solving style that balances delivery speed with long-term stability.

Bonus Experience

• Experience with streaming technologies such as Kafka or Kinesis for real-time data use cases.
• Exposure to ML tools and platforms like SageMaker, Vertex AI, or Databricks.
• Familiarity with BI and reporting tools such as Looker or Tableau.
• Interest in eCommerce behaviour, trading patterns, and customer analytics.

Why Join Kogan.com

• Be part of a culture that gives people ownership, autonomy, and the freedom to make a meaningful impact.
• Work with a strong team on challenges that help shape the future of eCommerce across Australia and New Zealand.
• Enjoy a role with minimal bureaucracy and significant responsibility.
• Contribute to a company recognised as one of the early pioneers of Australian eCommerce.
• Take an active role in shaping strategy at the company headquarters.
• Receive a learning budget of $1000.
• Access a variety of employee benefits, including Kogan First membership, team discounts, a health and wellness program, learning and development opportunities, lunch and learns, hackathons, a referral program, company and team events, celebrations, volunteering opportunities, and broad career development support.

Additional Information

To learn more about the company’s working style, technology stack, processes, and culture, you can review its careers and engineering blog resources.