Among computer and information systems managers, AI is already used for some of the tasks. Measured exposure for computer and information systems managers: 16% (some).

Share of this job’s tasks that AI is already used for at work, from real usage. It is not a forecast of job loss, and a low number means no use seen yet. Source: Anthropic Economic Index.

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About the job

The Systems Manager, GCP 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 (GCP)including data transfer, ingestion, transformation, curation, exposure, and activation.

In this role, you will lead the strategic build-out of scalable data pipelines to enable reliable downstream data activation for business stakeholders, analytics, and AI/ML model deployment. You will collaborate directly with solution architects, business system owners, and platform partners to deliver high-quality data products while maintaining hands-on depth in SQL, Python, Spark, and GCP-native serverless architecture. The ideal candidate blends outstanding technical, data engineering, and data modeling expertise with a proven track record of people management, fostering a culture of operational excellence, FinOps cost-efficiency, and rigorous data governance implementation.

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

Core Responsibilities Team Leadership & Development: Lead, mentor, and develop a technical, high-performing team of GCP data engineers, establishing work plans, setting performance metrics, and managing day-to-day agile execution

Hands-on Technical Leadership: Maintain deep technical expertise to guide architecture, review code, and directly assist with prototyping, troubleshooting, and unblocking complex pipeline issues

Data Ingestion & Transfer: Oversee the secure onboarding of diverse batch and streaming datasets from legacy on-premises systems and cloud sources into the landing zone of the platform

Data Transformation & Curation: Drive the design and development of performant, automated data transformations, establishing trusted, clean datasets via a structured medallion architecture (Bronze, Silver, Gold layers) using tools such as SQL, Python, and Dataform

Data Exposure & Activation: Lead the delivery of secure exposure layers (views, authorized datasets, APIs) that surface curated data products to business consumers, dashboard interfaces, and advanced AI systems (Enterprise Gemini/Vertex AI / Model & Agent Garden)

Pipeline Reliability & FinOps: Establish monitoring, alerting, and performance-tuning frameworks to ensure data pipelines are resilient, highly available, and cost-efficient. Coordinate closely with FinOps to identify spend anomalies and optimize GCP query and storage costs

Governance & Compliance Alignment: Implement and operationalize data quality rules, data classification, lineage tracking, and access controls in tight integration with the Data Governance team, ensuring compliance with privacy rules (PII, NERC CIP)

Collaborative Partnering: Act as the key liaison between data engineering, platform operations, legacy migration workstreams, and business stakeholders to align platform capabilities with immediate use cases

Required Education/Experience Master's Degree and a minimum of 6 years relevant full-time work experience or

Bachelor's Degree and a minimum of 8 years relevant full-time work experience

Preferred Education/Experience Master's Degree in Computer Science, Engineering, Math, Business, or a technology-centric field and a minimum of 6 years of relevant full-time work experience in GCP data engineering building scalable data pipelines, managing skilled teams, and delivering governed, cost-efficient data products for analytics and AI/ML

Relevant Work Experience 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, required

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 GCP, preferred

Skills and Abilities Effective leadership skills

Strong written and verbal communication skills

Possesses flexibility to work in a fast paced, dynamic environment

Demonstrated problem solving skills

Demonstrated time management and priority setting skills

Well organized, detail oriented and flexible to handle multiple assignments

Licenses and Certifications Driver's License Required

Other: Google Professional Data Engineer Preferred

Accredited Asset Management Specialist (AAMS) Google Professional Cloud Architect Preferred

Accredited Asset Management Specialist (AAMS) Technical certification(s) in IT 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

Mission Statement:

Consolidated Edison Company of New York, Inc. (Con Edison), Orange & Rockland Utilities (O&R), and Consolidated Edison Transmission (CET) employees are required to follow health, safety, and environmental policies, EEO, Standards of Business Conduct, and all other applicable company policy and procedures. We all share a responsibility to advance the company’s mission by excelling at our three corporate priorities – safety of our people and the public, operational excellence in all that we do, and ensuring the best possible customer experience.

Benefits:

We are dedicated to supporting the physical, mental, and financial health of our employees and their families. This commitment extends beyond the workplace to foster personal growth and holistic wellbeing. Our life-changing rewards package includes:

Rich medical & pharmacy benefits, including vision benefits

Dental benefits

Health Savings Accounts

Health Care and Dependent Care Flexible Spending Accounts

401(k) with robust matching

Employer paid Pension Plan

Employee Stock Purchase Plan with a generous matching contribution

State of the art Employee Assistance Program

Paid Parental Leave

Generous paid time off plus paid holidays

Family support: emergency backup child, & elder care assistance

Social responsibility and volunteer opportunities

Employee discount program

Commuter Benefits

Culture of growth and learning: career development; tuition reimbursement; recognition program

Life and Long-Term Disability Benefits

*Please be aware that some benefits may not apply to provisional or part-time job titles.