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Mid-level data engineer in metro with common toolset and known analytics brand increases competition.
Data engineering skills are broadly transferable, but required GCP and BigQuery experience raises specificity.
Explicit 5+ years and mandatory GCP/BigQuery/ETL tool experience narrows the candidate pool.
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Design, develop, and maintain large-scale data pipelines and ETL/ELT processes on Google Cloud Platform or equivalent.
Ensure production pipeline reliability through monitoring, troubleshooting, and managing deployments including off-hours support aligned to Australian time zones.
Lead technical architecture and delivery of AI-enabled enterprise software solutions, mentoring junior engineers, and collaborating with stakeholders to align technical direction with business goals.
5+ years of experience in end-to-end data engineering solutions design and implementation on Google Cloud Platform or comparable cloud platforms.
Proficiency in SQL and Python for data engineering tasks and experience with tools like BigQuery, Airflow/Argo Workflows, Dataflow, and Pub/Sub.
Bachelor's degree in Computer Science, Information Technology, or a related discipline.
Work Experience Required: 5+ years in relevant data engineering roles.
Experienced in leading technical design, code reviews, and delivery within agile, fast-paced environments and capable of driving engineering best practices and standards.
Strong hands-on expertise in cloud-native data engineering technologies with a strategic understanding of AI integration and engineering roadmaps.
Comfortable collaborating across time zones and mentoring junior engineers with proven ability to manage technical and stakeholder communication effectively.