21 Jun 2026

Data Engineer

Kogan.com

South Melbourne

21 Jun 2026

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Data Engineer

Kogan.com is seeking a Data Engineer to design and maintain data and ML pipelines, supporting data-driven decisions across marketing, purchasing, logistics, and finance. The role requires strong SQL, Python, and cloud experience, with a focus on scalable pipeline development and MLOps integration.

AI-enabledOn-siteFull-timeEntry LevelSQLApache Airflow

Data Engineer

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AI-enabledOn-siteFull-timeEntry LevelSQL

Salary

Not specified

Work Location

South Melbourne, Victoria, Australia, AU

Work Model

On-site

Employment Type

Full-time

Experience Level

Not Applicable

Core Qualifications

Technical (Must-have)

SQLApache AirflowdbtAWS GluePythonGCPGitCI/CDDockerBigQuerySnowflake

Soft Skills

Problem-Solving MindsetPractical approach

Preferred Qualifications

Technical (Nice-to-have)

Apache KafkaAmazon KinesisSageMakerVertex AIDatabricksLookerTableau

Key Responsibilities

•Design and maintain ETL/ELT pipelines handling 10M+ daily events and large-scale data transfers
•Develop and optimize data models in BigQuery or Snowflake for analytics and ML training
•Build underlying features and data inputs for Machine Learning models
•Develop and refine ML models for business use cases such as customer sentiment, churn prediction, demand forecasting
•Establish and maintain MLOps pipelines for automated deployment and monitoring of models
•Work with internal APIs and third-party tools for efficient data ingestion with data integrity
•Implement best practices for data quality, security, and documentation
•Develop according to software engineering best practices (Git, CI/CD, trunk-based development, tests)
•Contribute to experiments with AI and LLMs to solve business problems

Data EngineereCommerceRetailInformation TechnologySQLPythonGCPMachine LearningMLOpsOn-site

Key Responsibilities

•Design and maintain ETL/ELT pipelines handling 10M+ daily events and large-scale data transfers

•Develop and optimize data models in BigQuery or Snowflake for analytics and ML training

•Build underlying features and data inputs for Machine Learning models

•Develop and refine ML models for business use cases such as customer sentiment, churn prediction, demand forecasting

•Establish and maintain MLOps pipelines for automated deployment and monitoring of models

•Work with internal APIs and third-party tools for efficient data ingestion with data integrity

•Implement best practices for data quality, security, and documentation

•Develop according to software engineering best practices (Git, CI/CD, trunk-based development, tests)

•Contribute to experiments with AI and LLMs to solve business problems