Data Engineer - ML Pipelines & Data Platforms

Kogan.com; City of Melbourne; On-site; AUD 120,000 - 160,000; Full time

Benefits offered by this job

$1,000 learning budget

Kogan First membership

Team discounts

Health and wellbeing initiatives

Lunch & Learns

Hackathons

Referral bonuses

Volunteering opportunities

Regular team events

Job summary

Kogan.com is building a fast-moving data-driven engineering team in Melbourne to design and run data and ML pipelines powering Marketing, Purchasing, Logistics and Finance decisions.

As a Data Engineer you’ll craft scalable ETL/ELT pipelines, model data in BigQuery or Snowflake, and support ML workflows from feature generation to deployment. You’ll work with Airflow, dbt, AWS Glue, and Google Cloud, embracing CI/CD and best practices.

Qualifications

• Strong SQL skills for commercial-scale data products.
• Experience building and maintaining ETL/ELT pipelines.
• Experience with ML data workflows and features.
• Cloud data platforms, preferably GCP.
• Familiarity with data governance and quality practices.
• Proficient in Python for data engineering tasks.

Responsibilities

• Design and run data and ML pipelines for Marketing, Purchasing, Logistics and Finance.
• Develop scalable ETL/ELT pipelines handling 10M+ daily events.
• Model data in environments like BigQuery or Snowflake for analytics and ML training.
• Support ML workflows and feature inputs for models.
• Develop and refine ML models for business use cases such as sentiment, churn, demand forecasting.
• Establish MLOps pipelines for deployment and monitoring in production.
• Integrate with internal APIs and third-party tools while ensuring data integrity.
• Uphold data governance, quality, and documentation as a source of truth.

Skills

SQL Foundations

Python Proficiency

ML Engineering Exposure

Cloud Experience (GCP)

Problem-Solving Mindset

Software Engineering Practices

Tools

Airflow

dbt

AWS Glue

Docker

Git

CI/CD

Job description

Kogan.com is building a fast-moving data-driven engineering team in Melbourne to design and run data and ML pipelines powering Marketing, Purchasing, Logistics and Finance decisions.

As a Data Engineer you’ll craft scalable ETL/ELT pipelines, model data in BigQuery or Snowflake, and support ML workflows from feature generation to deployment. You’ll work with Airflow, dbt, AWS Glue, and Google Cloud, embracing CI/CD and best practices.