Systems Specialist - GCP Platform Engineer, Enterprise Data & Analytics

Consolidated Edison Company of New York; New York (NY); On-site; USD 140,000 - 190,000; Full time

Job summary

Consolidated Edison Company of New York is seeking a Systems Specialist, GCP Platform Engineer for Enterprise Data & Analytics. You will partner with development and solution engineering teams to ensure platform standards and governance are followed, and you will act as the final approver for code changes before deployment.

You will design backlog processes, shape the platform roadmap, and produce consumption/cost trend reports to support FinOps.

Qualifications

• Master's or Bachelor's degree in a technology-centric field with minimum years of relevant full-time work experience.
• Hands-on experience with Google Cloud Platform data/analytics workloads and core services like BigQuery, Dataflow, Pub/Sub, Cloud Storage.
• Experience with infrastructure-as-code (Terraform) and CI/CD (Azure DevOps) for GCP resources.

Responsibilities

• Own technical authority for the GCP platform stack; advise on design patterns and implementation approaches.
• Review and approve all code changes targeting the GCP platform prior to deployment, ensuring security and performance standards.
• Translate governance requirements into practical guardrails (IAM, configurations, deployment controls).
• Engage with platform users to keep the backlog grounded in real needs; shape the platform roadmap.
• Generate cost trend reporting and identify optimization opportunities for FinOps.
• Collaborate on architectural decisions affecting GCP services (BigQuery, Dataflow, Dataproc, Pub/Sub).

Skills

Strong communication

Python

SQL

Cloud data platforms

GCP expertise

Project management

Problem solving

Team collaboration

Education

Master's degree in Computer Science / Engineering / Math / Business

Bachelor's degree in Computer Science / Engineering / Math / Business

Tools

Terraform

Azure DevOps

Looker

dbt

Airflow/Composer

Kafka

BigQuery

Job description

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'll 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're deployed. You'll 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'll 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'll 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.

Responsibilities

Core 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 elevate 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

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


• Bachelor's Degree in Computer Science, Engineering, Math, Business, or technology-centric field and a minimum of 3 years relevant full-time work experience

Relevant Work Experience

• 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

Skills and Abilities

• Strong written and verbal communication skills


• 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

Licenses and Certifications

• 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

Physical Demands

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

Additional Physical Demands

• 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