Systems Manager, Google Cloud Platform Data Engineering, Enterprise Data & Analytics

Seeking a Systems Manager, Google Cloud Platform Data Engineering, Enterprise Data & Analytics, leads the hands-on technical team responsible for designing, building, and maintaining the enterprise-grade data pipelines that power the Enterprise Data & Analytics Platform (EDAP). This role manages a highly skilled team of engineers who own the core stages of the data lifecycle on Google Cloud Platform (Google Cloud Platform)-including data transfer, ingestion, transformation, curation, exposure, and activation, * Lead the platform tooling strategy, administration, and ongoing maintenance for the ED&A Data and AI platform team.

• Design, implement, and manage comprehensive monitoring and observability solutions across all Google Cloud Platform platform services.
• Develop and deliver consistent reporting on platform health, capacity, and usage metrics to stakeholders and leadership.
• Establish and oversee the triaging process for platform issues, ensuring rapid identification and accurate routing to the right owners for resolution.
• Enable, support, and maintain the platform’’'’s Model and Agent Garden ecosystem to support scalable ML and AI deployments.
• Lead and develop the Platform Tooling team, setting priorities, managing day-to-day execution, and fostering a culture of continuous improvement.
• Partner with data engineering, platform operations, and enterprise governance teams to align tooling capabilities with platform requirements and business use cases.
• Define and report on operational metrics, SLAs, and KPIs for platform tooling and observability.

• Required: Demonstrated experience in hands-on data engineering, pipeline architecture, or data platform operations, including time spent leading and managing technical teams.
• Required: Extensive hands-on experience designing, developing, and operating large-scale data pipelines on Google Cloud Platform, using services like BigQuery, Dataflow, Dataproc, Pub/Sub, Dataplex, and Cloud Storage.
• Required: Proficient in SQL, Python, or Spark for large-scale data processing and data modeling.
• Required: Solid experience with ETL/ELT pipeline design, workflow orchestration (e.g., Composer/Airflow), CI/CD pipelines (Azure DevOps preferred), and Infrastructure-as-Code (Terraform).
• Required: Experience defining and managing operational metrics, SLAs, and KPIs for enterprise-level data integration platforms.
• Preferred: Familiarity with implementing data governance frameworks, metadata management, and data quality testing tools (e.g., Great Expectations, Dataplex).
• Preferred: Background in utilities, energy, or other regulated industries with exposure to NERC CIP compliance, security protocols, and data classification.
• Preferred: Experience supporting migration initiatives moving data workloads off legacy ecosystems (such as Azure, Databricks, and C3.ai) onto Google Cloud Platform., * Master’’'’s Degree in Computer Science, Engineering, Math, Business, or a technology-centric field with a minimum of 6 years of relevant full-time work experience
• OR
• Bachelor’’'’s Degree in Computer Science, Engineering, Math, Business, or a technology-centric field with a minimum of 8 years of relevant full-time work experience.