Google Data Engineer - GCP

Responsibilities

• Design and Build: Develop, test, and maintain scalable data pipelines (ETL/ELT) using technologies like Dataflow (Apache Beam), Composer (Apache Airflow), and BigQuery.
• Infrastructure Management: Architect and optimize data models within BigQuery for performance and cost efficiency, supporting high-volume analytical workloads.
• Collaboration: Work closely with Data Scientists, Analysts, and Software Engineers to understand data needs and ensure data quality, integrity, and security across all platforms.
• Operational Excellence: Monitor and troubleshoot production data systems, implementing best practices for continuous integration and deployment (CI/CD) of data pipelines.
• Innovation: Explore and recommend new data technologies and cloud services to enhance data architecture and governance.
• Strong background and experience in Google (GCP) along with a background as a Data Engineer.
• Experience with real-time streaming data processing using technologies like Pub/Sub and Dataflow Streaming.
• Familiarity with containerization and orchestration tools (e.g., Docker, Kubernetes).
• Experience with version control systems (e.g., Git).
• Deep understanding of DataOps principles and automated testing for data quality.
• GCP Professional Data Engineer Certification is a plus.
• Previous experience in a similar role as a Cloud Engineer developing, implementing or managing secure Google Cloud solutions at an enterprise level
• Previous hands on Google Cloud experience
• Previous experience building infrastructure as code with Terraform at an advanced level
• Ability to script in at least one of the following languages: Python, Bash
• Applied knowledge of CI/CD concepts and deployment of platform solutions
• Solutions experience leveraging GCP-based core services such as Compute Engine, App Engine, Kubernetes Engine, Cloud Storage, BigQuery, Pub/Sub, etc.
• Be well-versed in networking concepts, including virtual private clouds (VPCs), subnets, load balancing, firewalls, and DNS
• Experience designing secure and scalable network architectures on Google Cloud
• Security-focused with a deep understanding of cloud security principles, threats, and mitigation techniques
• Hold one more of the following Professional Level Google Cloud certifications: Cloud Architect, Cloud DevOps Engineer, Cloud Developer or other professional-level Google Cloud certifications
• Why join us:
• At NCS Australia, we are committed to supporting adjustments throughout the recruitment and selection process, as well as during employment. We actively support and encourage people with disability to apply.
• Agencies:
• We've got this. We request that

Benefits

Additional Information

This role is responsible for building and scaling the massive, reliable data infrastructure that powers critical decisions, product features, and advanced analytics across our organization-impacting billions of users daily. As a Data Engineer, you will be a core architect and builder of our next-generation data pipelines, transforming raw, high-volume data into structured, actionable insights. You will design, construct, implement, and rigorously manage end-to-end data processing systems, focusing on robustness, efficiency, security, and high throughput. Your challenge will be to translate complex, ambiguous business requirements from product managers and data scientists into scalable, fault-tolerant solutions using cutting-edge Google Cloud Platform (GCP) technologies. This includes deep involvement with services like BigQuery, Dataflow, Cloud Composer, and Pub/Sub. Your contributions will be instrumental in enabling data-driven optimization across areas such as product development, machine learning model training, and operational efficiency, making you a vital partner in Google's ongoing innovation. We're looking for an engineer ready to tackle petabyte-scale data challenges and champion data quality across the enterprise.

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