Lead the strategy and execution of complex and large Global Specialty 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
Implementing 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
Oversee the design, development, and maintenance of data pipelines, data warehouses, data lakes and reporting systems
Build, mentor, and lead a high-performing team including 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 and recommend innovative tools and technologies to enhance data capabilities enabling business strategy
Define and implement robust data management frameworks to ensure successful adoption of Enterprise Data Governance and Data Quality practices
Effectively manage the budget and financials for GS Data and Analytics portfolio
Requirements
15+ 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
5+ years in senior leadership roles managing large and complex data and analytics portfolio with a people budget of at least $10M
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, data warehouse, data integration, data lakes, data domains, data products, 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
Benefits
Other rewards may include short-term or annual bonuses
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