Systems Manager - GCP Data Engineering, Enterprise Data & Analytics

Con Edison Co.; New York (NY); On-site; USD 150,000 - 190,000; Full time

Job summary

Con Edison Co. seeks a Systems Manager, GCP Data Engineering, to lead a skilled team responsible for enterprise data pipelines on Google Cloud Platform for the EDAP.

You will drive scalable pipelines, collaborate with architects and stakeholders, and maintain hands‑on depth in SQL, Python, Spark, and GCP-native serverless architecture. The ideal candidate blends technical, data engineering, and people-management excellence with a focus on governance and cost-efficiency.

Qualifications

• Hands-on data engineering with cloud-scale pipelines.
• Experience leading and developing engineers.
• Strong SQL, Python, Spark and data governance practices.

Responsibilities

• Lead a hands-on data engineering team to design, build and maintain enterprise data pipelines on GCP.
• Collaborate with solution architects and stakeholders to deliver data products for analytics and AI/ML deployment.
• Ensure data governance, FinOps cost-efficiency and operational excellence.

Skills

SQL

Python

Spark

GCP

Job description

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.