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Energy Jobline ZR

Senior Manager, Data Engineering (AI enablement, context engineering) in San Jose

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Job Description

We’re looking for a Senior Manager, Data Engineering to lead a high-performing data engineering team and drive the design and implementation of scalable, secure, and modern enterprise data platforms. This is an excellent opportunity for a hands-on technical leader passionate about cloud data engineering, lakehouse architecture, DataOps, and AI/advanced analytics enablement.

Note: Experience in AI enablement for context engineering and ML models including causal and colinear modeling

Location: San Jose, CA

Type: Direct Hire

Key Responsibilities

  • Architect and implement scalable cloud-based Lakehouse/Warehouse solutions using Databricks and AWS
  • Design, optimize, and govern enterprise data models, including dimensional modeling and semantic layers
  • Build and maintain high-performance batch and real-time data pipelines using ETL/ELT and streaming technologies
  • Establish robust data quality frameworks, monitoring, and validation processes
  • Implement CI/CD pipelines and DataOps best practices for automated, secure, and reliable deployments
  • Establish data governance, including data cataloging, lineage, metadata management, and standards
  • Design and implement strong data security, access controls, and governance frameworks
  • Build scalable data foundations supporting AI, automation, machine learning, and advanced analytics
  • Lead, mentor, and develop a team of Data Engineers, establishing technical standards and engineering best practices
  • Partner cross-functionally with business and technology stakeholders to promote data excellence, accountability, and continuous innovation

Must-Have Qualifications

  • 10+ years of experience in Data Engineering, Data Architecture, or related fields
  • 5+ years of experience leading and developing technical teams
  • Deep expertise in SQL, cloud data platforms, and distributed data processing
  • Strong hands-on experience with modern cloud data platforms such as:
  • Databricks
  • Snowflake
  • AWS Redshift
  • Google BigQuery
  • Strong experience with ETL/ELT tools, particularly Alteryx and Informatica
  • Strong understanding of data modeling, including dimensional modeling and semantic layers
  • Experience with data orchestration, workflow management, and automated data pipelines
  • Proven ability to architect and deliver scalable, secure, highly available, and reliable enterprise data solutions
  • Strong technical leadership, communication, mentoring, and cross-functional collaboration skill

Skills

What Senior Data Engineering jobs ask for — and how much of it you have →
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See also

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