Systems Manager - Google Cloud Platform, Enterprise Data & Analytics

Overview

The Systems Manager, Google Cloud Platform, Enterprise Data & Analytics, leads the strategy, delivery, and operational excellence of Con Edisons enterprise data platform on Google Cloud. This role provides end-to-end ownership of data ingestion, governance, and platform performance to ensure that enterprise data is reliable, secure, and ready to support analytics, regulatory reporting, and advanced AI/ML initiatives.

The Systems Manager oversees the engineering, architecture, and operations of Google BigQuery, Vertex AI / Agent Platform, Dataplex / Knowledge Catalog and associated data intake services, ensuring adherence to enterprise standards for reliability, scalability, and cost efficiency. This includes managing the full data lifecycle from intake and transformation to consumption while maintaining strong controls around data quality, security, and privacy. Partnering with Data Governance, Analytics, AI/ML, and Application teams, this role translates enterprise data strategy into production-grade solutions that power business insights and grid modernization. The position also manages internal staff and external vendors to deliver continuous improvement and operational resilience across Con Edisons data ecosystem.

This position does not provide employment pursuant to the terms of a STEM OPT Training Plan.

Responsibilities

• Own and manage the Google enterprise data platform, including datasets, schemas, environments, and supporting services (e.g. BigQuery, Vertex AI / Agent Platform, Dataplex / Knowledge Catalog)
• Lead and oversee enterprise data intake and establish standardized data onboarding patterns, including batch and streaming ingestion pipelines, ensuring reliability, scalability, and timeliness
• Define and enforce platform standards for data modeling, partitioning, clustering, transformation patterns, and development best practices
• Enable analytics, reporting, and data engineering teams to develop and deploy data products efficiently within BigQuery
• Ensure day-to-day operational excellence of the BigQuery platform, including monitoring, alerting, incident response, and root cause analysis
• Partner with Data Governance and Security teams to enforce data access controls, privacy requirements, retention policies, and auditability within Dataplex / Knowledge Catalog
• Ensure data quality controls and validation processes are embedded within ingestion and transformation workflows
• Manage, lead and develop platform engineering and operations staff supporting BigQuery and data intake services through coaching, performance management, and effective work assignment
• Execute the enterprise data platform roadmap by operationalizing approved standards and architectural decisions
• Identify opportunities to improve platform reliability, cost management / optimization, automation, and developer experience for continuous improvement across the data platform in an agile manner

Qualifications

• Master's Degree in Computer Science, Engineering, Math, Business, or technology-centric field and a minimum of 6 years relevant full-time work experience or
• Bachelor's Degree in Computer Science, Engineering, Math, Business, or technology-centric field and a minimum of 8 years relevant full-time work experience

• Demonstrated experience leading enterprise data platform strategy, engineering, and operations on GCP, with deep expertise in BigQuery and one or more of Dataplex / Knowledge Catalog and Vertex AI / Agent Platform, other AI / ML / LLM / Analytics GCP services, required
• Proven end-to-end ownership of enterprise data platforms, including data ingestion, transformation, governance, and performance management, required
• Hands on experience overseeing BigQuery architecture, capacity planning, performance optimization, and cost management in large scale environments, required
• Ability to communicate platform health, risks, cost posture, and delivery progress to senior leadership and enterprise stakeholders, required
• Proven track record implementing and operating secure data ingestion and intake services with strong controls for access management, encryption, and auditability, preferred
• Strong background designing and operating scalable, reliable, and cost-efficient data platforms that support analytics, regulatory reporting, and AI and ML initiatives, preferred
• Demonstrated ability to enforce enterprise standards for data quality, security, privacy, and compliance across the full data lifecycle, preferred
• Experience partnering closely with Data Governance, Analytics, AI and ML, and Application teams to translate enterprise data strategy into production grade solutions, preferred
• Experience managing internal engineering teams and external vendors, including delivery planning, performance management, and continuous improvement initiatives, preferred
• Demonstrated experience operating mission critical data platforms with high availability, operational resilience, and well-defined incident and recovery processes, preferred

• Strong written and verbal communication skills
• Builds and manages effective teams
• Possesses flexibility to work in a fast paced, dynamic environment
• Ability to work within tight timeframes and meet strict deadlines
• Demonstrated problem solving skills
• Effective interpersonal skills
• Ability to drive multiple projects to successful completion
• Demonstrated time management and priority setting skills
• Ability to simultaneously handle multiple priorities
• Well organized, detail oriented and flexible to handle multiple assignments

• Driver's License Required
• Other: Technical certification(s) in IT Preferred
• Other: Google Professional Cloud Architect Preferred
• Other: Google Professional Data Engineer Preferred
• Other: Google Associate Cloud Engineer Preferred

• Sit or stand to use a keyboard, mouse, and computer for the duration of the workday

• The selected candidate will be assigned a System Emergency Assignment (i.e., an emergency response role) and will be expected to work non-business hours during emergencies, which may include nights, weekends, and holidays.
• Available to work off hours as operationally required