Data Engineer

Role Summary

We are looking for an experienced GCP Data Engineers to join a leading AI & Data practice, designing, building, and maintaining scalable data platforms and data pipelines on Google Cloud Platform (GCP).

Working across cloud, data, analytics, and AI transformation programs, you will collaborate with architects, product teams, engineers, and business stakeholders to develop secure, reliable, and high-performing data solutions. This role offers the opportunity to work across the full data engineering lifecycle, supporting enterprise data platforms, DataOps automation, CI/CD delivery, and modern analytics capabilities.

Contract Summary

• Rate: Based on experience
• Clearance: Baseline or above
• Employment Type: 12 month Contract or Permanent
• Work Model: Hybrid
• Location: Melbourne (Preference) will also look at Canberra and Brisbane

Responsibilities

• Design, develop, test, and maintain scalable data pipelines and data platform solutions on Google Cloud Platform.
• Translate functional and technical requirements into detailed data engineering designs.
• Build and maintain ELT/ETL frameworks supporting enterprise data integration and transformation.
• Develop batch and real-time data ingestion, processing, and integration pipelines.
• Design and optimise cloud-native data storage and processing solutions.
• Collaborate with business stakeholders, architects, product teams, and engineers to deliver high-quality data engineering outcomes.
• Troubleshoot and resolve complex data engineering and platform issues.
• Develop, implement, and support DataOps automation and CI/CD pipelines for data solutions.
• Automate the development, testing, deployment, and monitoring of data pipelines.
• Monitor, optimise, and improve data processing performance, scalability, and reliability.
• Ensure data quality, integrity, accuracy, and availability across enterprise data platforms.
• Support data governance, metadata management, security, and compliance initiatives.
• Promote engineering best practices, reusable frameworks, and continuous improvement across delivery teams.
• Key Technologies: Google Cloud Platform (GCP), BigQuery, Dataflow, Dataprep, Cloud Storage, Pub/Sub, Cloud Composer, SQL, Python, Java, Scala, ELT, ETL, CI/CD, DataOps, BigQuery, Snowflake, Teradata, Oracle Exadata, Azure Synapse, Data Warehousing, Data Modelling.

Skills & Experience

• 3–5+ years' experience delivering data engineering solutions on Google Cloud Platform (GCP).
• Experience designing, developing, and maintaining enterprise data pipelines and cloud data platforms.
• Strong experience with GCP services including BigQuery, Dataflow, Dataprep, Cloud Storage, and other GCP-native data engineering services.
• Experience building and supporting batch and real-time ELT/ETL pipelines.
• Strong SQL development skills and experience working with complex data structures.
• Strong programming skills in Python, Java, or Scala.
• Experience implementing DataOps practices, CI/CD pipelines, and deployment automation.
• Experience with physical data modelling, data warehousing, and enterprise data integration.
• Experience working with data warehouse platforms such as BigQuery, Snowflake, Teradata, Oracle Exadata, Azure Synapse, or similar technologies.
• Strong understanding of data governance, security, data quality, and metadata management.
• Excellent analytical, problem-solving, stakeholder engagement, and communication skills.
• Experience working within Agile, multidisciplinary delivery teams.

Highly Regarded

• Google Cloud Professional Data Engineer certification.
• Experience working within government or highly regulated industries.
• Experience with Infrastructure as Code (Terraform), DevOps, and cloud automation.
• Experience mentoring junior engineers or contributing to engineering capability uplift.
• Experience supporting enterprise analytics, AI, or machine learning platforms.