Director, Data Architect

Primary Job Responsibilities

• Lead the strategy and execution of complex and large Data and Analytics portfolio.
• Develop and implement a strategic roadmap to modernize legacy data and analytics ecosystems using Cloud and AI.
• Solve for data complexity by enabling data domains and data products for all consumption architypes and stakeholders including reporting, data science, AI/ML and analytics.
• Ensure data architecture and solutions align with enterprise-wide standards for Data, AI and Analytics.
• Effectively communicate strategy, execution progress, and outcomes to diverse stakeholders and promote data capabilities through thought leadership and presentations.
• Implement AI data pipelines that integrate structured, semi-structured, and unstructured data to support AI and Agentic solutions.
• Design, build and maintain scalable real-time data pipelines for efficient ingestion, processing, and delivery.
• Drive best practices in AI data engineering by establishing standardized processes, promoting cutting-edge technologies, and ensuring data quality and compliance across the enterprise.
• Oversee the design, development, and maintenance of lakehouse architectures, data pipelines, data warehouses, data lakes and reporting systems.
• Expertise in data engineering practices, knowledge of AI technologies, and the ability to lead cross-functional teams.
• Expertise in real-time data streaming, agentic frameworks, Data APIs, vector stores, and RAG architectures, self-serve analytics and AI.
• Mentor and lead a high-performing team including Directors, Business data analysts, Data engineers and Release train engineers.
• Identify and champion developer productivity improvements across the end-to-end data management lifecycle.
• Stay current with emerging trends in data engineering and AI/ML, design prototypes and conduct experiments, and recommend innovative tools and technologies to enhance data capabilities enabling business strategy.
• Support robust data management frameworks to ensure successful adoption of Enterprise Data Governance and Data Quality practices.
• Develop deep partnerships and alignment with the portfolio and agile value stream frameworks.
• Experience with Agile at Scale and iterative development through cross-functional teams.
• Partners with Technology, Data, AI Platform, EB Ops and Architecture teams to influence technology, data, platform and tooling strategy.

Qualifications

• Candidates must be authorized to work in the US without company sponsorship.
• The company will not support the STEM OPT I-983 Training Plan endorsement for this position.
• 12+ years in data engineering, data management and building large-scale data ecosystems.
• Bachelor's or Master’s degree in Computer Science, Data Science or a related field.
• 7+ years in leadership roles managing large and complex data and analytics portfolio with large size teams.
• Proven strategic and innovative thinker with a track record of enabling transformative data capabilities.
• Mastery level data engineering and architecture skills, including deep expertise in data architecture patterns, lakehouses , data integration, data domains, data products, conversational business intelligence, and cloud technology capabilities.
• Technical expertise in LLMs, AI platforms, prompt engineering, LLM optimization, Retrieval-Augmented Generation (RAG) architectures and vector database technologies (Vertex AI, Postgres, OpenSearch, Pinecone etc.).
• Strong experience with GCP, Vertex AI or AWS required.
• Experience in multi cloud environment.
• Experience in Lang chain, AI agents, Vertex AI and Google Agent ecosystem.
• Strong experience with the design and development of complex data ecosystems leveraging next-generation cloud technology stack across AWS or GCP Cloud and Snowflake.
• Exceptional presentation and verbal/written communication skills; must be able to communicate effectively at all levels across the organization.
• Ability to lead successfully in a lean, agile, and fast-paced organization, leveraging Scaled Agile principles and ways of working.
• Excellent negotiation, influencing, and conflict resolution skills; adept at building strong cross-functional relationships.