Design, build, and optimise scalable, reliable data pipelines across cloud platforms (AWS, GCP, Azure)
Work with modern data technologies such as Databricks, Snowflake, cloud data lakes, and orchestration tools
Develop high-quality data models to support analytics, reporting, and AI use cases
Collaborate with clients to translate business requirements into well-structured, actionable data solutions
Implement data ingestion, transformation, storage, and access layers across multi-cloud environments
Support or implement dbt, CI/CD, and engineering best practices across projects
Ensure strong data quality, governance, lineage, and performance practices
Contribute to reusable components, accelerators, and internal engineering frameworks
Work closely with cross-functional consultants, analysts, and architects to deliver cohesive solutions
Mentor junior engineers and positively influence client delivery

4–6+ years’ experience in data engineering or analytics engineering
Strong hands-on experience with Databricks, and at least one major cloud platform (AWS, GCP, or Azure)
Solid SQL capability and experience building complex data transformations
Familiarity with modern data stacks
e.g., Snowflake, dbt, Delta Lake, cloud ETL/orchestration tools
Experience working across the full data lifecycle: ingestion → transformation → modelling → consumption
Consulting, stakeholder-facing experience, or cross-functional delivery exposure
Knowledge of DevOps concepts, version control, and/or CI/CD in data environments
Excellent communication, problem-solving, and collaboration skills
Melbourne-based, with ability to work on-site with clients as required
A mindset of curiosity, delivery excellence, and continuous learning

Consultant – Data Engineer

Key skills