VP Data Engineering and Architecture

Build the data foundation powering AI, automation, and enterprise intelligence

Vice President of Data Engineering & Architecture

The ideal candidate brings deep expertise in architecting large-scale data warehouses and data lakes, with a strong command of OLAP and OLTP principles, and a passion for building modern, intelligent data platforms.

Key Responsibilities

Strategic Data Architecture

• Design and implement scalable, high-performance enterprise data architectures — including data warehouses (AWS Redshift, SQL Server) and structured/unstructured data lakes.
• 
  
• Develop forward-looking architectural blueprints that seamlessly support analytics, operational systems, and AI workloads.

End-to-End Data Engineering

• Lead the design, build, and maintenance of robust data pipelines and enterprise integration frameworks.
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• Ensure data is accurate, consistent, discoverable, and accessible across all business domains.

Performance Engineering

• Apply deep OLTP and OLAP expertise to optimize database design, query performance, and workload throughput.
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• Drive continuous improvement in data platform efficiency, scalability, and resilience.

Cross-Functional Collaboration

• Work closely with automation, AI, analytics, and software engineering teams to align data strategy with business outcomes.
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• Integrate data systems into intelligent workflows powering automation and AI adoption.

Data Modeling & AI Enablement

• Architect scalable semantic and analytical data models optimized for natural-language querying and AI-driven analytics.
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• Enable clean, well-structured data for business intelligence platforms (Power BI and others).

Governance & Data Quality

• Establish enterprise data governance, metadata management, and data quality standards.
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• Operationalize master data management, ensuring consistency, compliance, and trusted enterprise data assets.

Leadership & Talent Development

• Build, mentor, and scale a high-performing team of data engineers and architects.
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• Foster a culture centered on innovation, reliability, automation, and excellence.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Information Systems, Data Engineering, or related field.
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• 14+ years of progressive experience in data engineering or data architecture within enterprise environments.
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• Proven ability to architect and deliver large-scale data warehouses and data lakes using 

  AWS Redshift and/or SQL Server

  .
• 
  
• Deep understanding of 

  OLAP/OLTP systems

  , data modeling, and performance optimization.
• 
  
• Advanced proficiency in 

  SQL

   and enterprise data integration practices (ETL/ELT, APIs, streaming pipelines).
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• Hands-on experience with 

  Power BI

   or similar enterprise BI platforms.
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• Exposure to 

  AI/ML data preparation, semantic modeling, and natural-language query enablement

   preferred.
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• Strong communication and stakeholder-management skills; ability to influence technical and business leaders.
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• Demonstrated track record partnering cross-functionally with automation, analytics, and software engineering teams.