Data Engineer Manager at PwC focusing on building data infrastructure and solutions. Leading data engineering projects to transform raw data into actionable insights and drive business growth.
About the role
- Vice President of Strategic Data Architecture overseeing data architecture for a group of companies. Defining, governing, and advancing the data ecosystem to align with business priorities.
Responsibilities
- Establish and maintain the enterprise data architecture vision, including conceptual, logical and physical models, data flows, storage patterns, and integration frameworks
- Create and maintain a comprehensive inventory of current state data capabilities across all business units
- Define the target state architecture and align stakeholders on the required data product capabilities and technical foundations
- Define and integrate already architectural patterns that support enterprise AI, Generative AI, and Agentic AI use cases, ensuring scalable and governed deployment across the ecosystem
- Partner closely with leaders across Data Management, Data Governance, Data Product, Data Engineering, Analytics, and Product teams to translate business needs into data driven solutions
- Collaborate with AI/ML teams to shape enterprise AI strategies, ensuring data architecture enables model development, model operations (MLOps), vector storage, retrieval augmented generation (RAG), and agent-oriented workflows
- Identify opportunities to simplify, consolidate, or modernize legacy technologies, data stores, and applications
- Oversee the design of scalable architectures that support enterprise-wide data products and shared capabilities across multiple business units and group-level functions
- Lead the development and enforcement of data architecture standards, quality frameworks, and governance policies
- Incorporate AI governance standards, including model transparency, lineage, auditability, responsible AI practices, and controls for Generative AI and Agentic AI solutions
- Stay current with emerging technologies, architecture patterns, and industry best practices.
Requirements
- Bachelor’s degree in Computer Science, Information Technology, Data Science, or a related field
- Master’s degree or relevant professional certifications (e.g., CDMP, CIMP) strongly preferred
- 10+ years of experience in data management, data governance, or related disciplines within SaaS or cloud based environments
- Extensive background in enterprise data architecture, cloud solutions, data modeling, data warehousing, data lakes, data marts, and BI ecosystems
- Proven success designing and implementing architectures that deliver data as a product for internal and external stakeholders
- Strong understanding of structured and unstructured data management, data integration, data lifecycle management, and modern data platforms
- Experience working with Scaled Agile or similar methodologies
- Proficiency in AI architectural patterns, data preparation for AI/ML, and designing systems that support LLMs and Agentic AI workflows
- Expertise in cloud data platforms and tools (e.g., AWS, Snowflake, Redshift, Azure, Google Cloud, MDM, ETL/ELT tools)
- Deep knowledge of data governance frameworks, data management principles, and industry standards (ISO 27001, SOC 2)
- Strong understanding of data privacy and compliance requirements (GDPR, CCPA, emerging AI related)
- Advanced analytical, problem-solving, organizational, and system design skills.
Benefits
- health insurance (medical, dental, vision)
- a retirement savings plan
- paid time off
- other employee benefits
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