Systems Specialist - GCP Platform Engineer, Enterprise Data & Analytics

Overview

The Systems Specialist, GCP Platform Engineer, Enterprise Data & Analytics serves as the subject matter expert for the Google Cloud Platform stack for AI and Analytics. In this role, you will partner with development and solution engineering teams to ensure solutions are built in line with platform standards and governance requirements, acting as the final approver for all code changes before they are deployed.

You will maintain a healthy platform backlog driven by user engagement and feedback, coordinate the platform feature roadmap, and manage prioritization and scheduling for feature enablement and implementation aligned towards delivering value for our business partners and stakeholders. Beyond day-to-day platform stewardship, you will design and implement processes for tracking usage metrics and cost trend reports for the financial operations team to support cost accountability and transparency, and monitor and report on platform data quality and governance, surfacing issues and recommendations to the right teams.

You will contribute to overall platform data architecture decisions in collaboration with the platform data architect, with scope shaped by the GCP stack, and step into hands-on development work when needed. This position does not provide employment pursuant to the terms of a STEM OPT Training Plan.

• 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 Fin Ops 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 Big Query, 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

• Required Education/Experience - Master s Degree in Computer Science, Engineering, Math, Business, or technology-centric field and a minimum of 2 years relevant full-time work experience or
• J540 Bachelor s Degree in Computer Science, Engineering, Math, Business, or technology-centric field and a minimum of 3 years relevant full-time work experience

• Hands-on experience designing and operating data and analytics workloads on Google Cloud Platform, including core services such as Big Query, Dataflow, Dataform, Pub/Sub, Cloud Storage, and IAM, required
• Proficiency with infrastructure-as-code (Terraform preferred) and CI/CD pipelines (Azure Dev Ops 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 Fin Ops 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

• Strong written and verbal communication skills
• Flexibility to work in a fast paced, dynamic environment
• Ability to work within tight…