Data Engineer

Job Description

DataMinds Analytics is looking for a Data Engineer for our fully remote Australian team building the data platforms our clients depend on. You will design batch and streaming pipelines with Spark, dbt and Airflow, model data warehouses in Snowflake and BigQuery, and ensure data engineers everywhere would be proud of the reliability you deliver. Our Australian clients include major retailers and utilities, whose nightly pipelines you will own — processing terabytes that power next-morning trading and operational decisions.

Remote-first is in our DNA: async standups, documented decisions, and quarterly onsites in Sydney or Melbourne. You will own critical infrastructure, mentor junior engineers, and work with modern tooling throughout. You will also design our streaming reference architecture with Flink, lead data-modelling reviews across squads, and receive funded Google Professional Data Engineer certification.

Responsibilities

Build batch and streaming data pipelines with Spark, dbt and Airflow
Design and maintain data warehouses on Snowflake and BigQuery
Implement data quality checks and observability frameworks
Optimise pipeline performance and cloud cost efficiency
Partner with analysts and scientists on data modelling needs
Document architectures and mentor junior data engineers

Requirements

3-5 years of professional data engineering experience
Strong Python and SQL skills
Hands-on experience with Spark, dbt and Airflow
Data warehouse modelling (Kimball/dimensional) expertise
Cloud experience (AWS, GCP or Azure)
Familiarity with streaming (Kafka, Flink) preferred

Skills

Python, SQL, Apache Spark, dbt, Airflow, Snowflake, Kafka, AWS, Data Modelling, Git

Benefits

Fully remote within Australia
Annual bonus and share scheme
Home-office setup budget
Comprehensive health insurance
Professional development budget