Data Engineer

NEP Group

48d•Hybrid

About The Position

Were looking for an experienced Data Engineer to help design, build, and optimize modern data pipelines that power analytics, BI, and machine learning across NEP Group. In this role, youll develop scalable ETL/ELT workflows feeding Snowflake and Databricks, collaborate closely with BI and ML teams, and continuously improve our data platform to support a growing global organization. If you enjoy working with large datasets, modern cloud tools, and solving complex data challenges, this is a chance to make a real impact. Preference is for this to be a hybrid role in either Sydney or Melbourne.

Requirements

5+ years of experience in data engineering with strong Python, SQL, and Spark skills
Hands-on experience building and automating ETL/ELT pipelines and working with data warehouses
Solid understanding of data modeling, schema design, and performance optimization
Experience with cloud-based data platforms such as Databricks and modern storage solutions (e.g., Delta Lake)
Familiarity with CI/CD, data versioning, and best practices for scalable data infrastructure
Knowledge of data governance, data quality, and lineage concepts
Understanding of cloud cost optimization, security, and access control best practices

Responsibilities

Design, develop, and automate ETL/ELT pipelines feeding Snowflake and Databricks
Build and maintain scalable ingestion pipelines using dbt, Databricks, and Fivetran
Optimize queries, data partitioning strategies, and schema design for performance and cost
Partner with BI and ML teams to support analytics and advanced data use cases
Identify opportunities to improve data infrastructure and implement best-practice solutions
Troubleshoot data issues and provide technical guidance and support
Contribute to ongoing improvements in reliability, scalability, and data quality