Senior Manager, Data Engineering (AI enablement, context engineering)

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