Systems Specialist - GCP Platform Engineer, Enterprise Data & Analytics

Responsibilities

• Own technical authority for the GCP platform stack, advising development and solution engineering teams on design patterns, service selection, and implementation approaches that fit the platform's capabilities and constraints through review of solution architecture / design documents for AI / ML / Analytics use cases.
• Review and approve all code changes targeting the GCP platform prior to deployment, validating alignment with security, performance, and architectural standards across environments.
• Translate platform governance requirements into practical guardrails, including IAM policies, resource configurations, and deployment controls that teams can adopt without slowing delivery.
• Run continuous discovery with platform users (business and developers) through office hours, intake channels, and direct engagement to keep the backlog grounded in real needs rather than assumptions.
• Shape and publish the GCP platform roadmap, balancing user-requested features, technical debt, and strategic initiatives into a sequenced delivery plan.
• Generate consumption and cost trend reporting for the FinOps team, identifying spend anomalies, optimization opportunities, and chargeback inputs that drive accountability across consuming teams.
• Track data quality and governance posture on the platform, including lineage gaps, access patterns, and policy violations, and escalate findings to the teams positioned to act on them.
• Collaborate with the platform data architect on architectural decisions affecting the GCP stack, contributing depth on services like BigQuery, Dataflow, Dataproc, Pub/Sub, Dataplex / Knowledge Catalog and Vertex AI / Agent Platform.
• Build and maintain reference implementations, infrastructure-as-code modules, and documentation that help teams onboard to the platform quickly and consistently.
• Step into hands-on engineering work on the GCP stack as needed, whether unblocking a delivery team, prototyping a new capability, or remediating a production issue.

Qualifications

• Hands-on experience designing and operating data and analytics workloads on Google Cloud Platform, including core services such as BigQuery, Dataflow, Dataform, Pub/Sub, Cloud Storage, and IAM, required.
• Proficiency with infrastructure-as-code (Terraform preferred) and CI/CD pipelines (Azure DevOps preferred) for deploying and managing GCP resources at scale, required.
• Experience reviewing code and architectural designs against platform standards, with the ability to provide clear, actionable feedback to engineering teams, required.
• Strong scripting or development skills in Python, SQL, or a comparable language used in data engineering workflows, required.
• Familiarity with FinOps practices, including cloud cost monitoring, chargeback or showback models, and optimization techniques specific to GCP, preferred.
• Exposure to adjacent platforms or tools in a modern data stack such as Looker, dbt, Airflow/Composer, or event streaming technologies like Kafka, preferred.
• Working knowledge of data governance concepts including access controls, data classification, lineage, and quality monitoring within a cloud data platform, preferred.