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Systems Manager - GCP Data Engineering, Enterprise Data & Analytics

IT Solutions Delivery
New York City, USA
Full-time
Manager · 8+ years experience
Onsite
Discovered 6 days ago
GCPSQLPythonAzureCommunicationWorkday

Full Job Posting

Qualifications

  • 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

Responsibilities

  • 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

Preferred Qualifications

  • Preferred Education/Experience
  • 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
  • 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
  • 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

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