AVP, AI Data Engineering, Customer Data Ecosystem

AVP Data Engineering - GE05AE

We’re determined to make a difference and are proud to be an insurance company that goes well beyond coverages and policies. Working here means having every opportunity to achieve your goals – and to help others accomplish theirs, too. Join our team as we help shape the future.

• Hybrid or Remote work schedule available.
• Candidates living near one of our office locations are expected to work in an office 3 days a week (Tuesday through Thursday).
• Remote candidates can work from home, with expectation to visit the office as business needs arise.
• Must be eligible to work in the U.S. without company sponsorship.

• Lead the strategy and execution of complex and large Data and Analytics portfolio.
• Ensure data architecture and solutions align with enterprise‑wide standards for Data, AI, and Analytics.
• Communicate strategy, execution progress, and outcomes to diverse stakeholders, promoting 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.
• Define and operationalize ontologies, context graphs, and knowledge graphs across domains to power reasoning, explainability, and decision intelligence.
• Lead the design and execution of enterprise‑scale semantic layers to standardize business meaning and enable trusted analytics, AI, and Agentic use cases.
• Enable semantic‑first AI and Agentic analytics, ensuring LLMs and agents can consume governed business context, metrics, and rules.
• Drive production‑scale execution of semantic and knowledge platforms with strong standards for performance, governance, security, and lifecycle management.
• Drive best practices in AI data engineering by establishing standardized processes, promoting cutting‑edge technologies, and ensuring data quality and compliance across the enterprise.
• Build, mentor, and lead a high‑performing team of directors, business data analysts, data engineers, and release‑train engineers.
• Identify and champion AI‑augmented productivity improvements across the end‑to‑end data management lifecycle.
• Maintain current knowledge of emerging trends in Agentic AI and data engineering, leading proof‑of‑concepts and early pilots for emerging data and AI technologies.
• Define and implement robust data governance, stewardship, and quality frameworks to ensure successful adoption of enterprise data governance and data quality practices.
• Effectively manage portfolio budget and financials, and align with agile value‑stream frameworks.
• Partner with technology, data, AI COE, applied AI, and architecture teams to influence technology, data, platform, and tooling strategy.
• Evangelize Agentic Data Engineering, driving adoption through patterns, playbooks, and real‑world deployments across the enterprise.

• 12+ years in data engineering, data management, and building large‑scale data ecosystems.
• 7+ years in senior leadership roles managing complex data and AI portfolios with hands‑on experience.
• Deep expertise in data architecture patterns, lake houses, data integration, data domains, and data products.
• Mastery of scalable AI‑driven data systems supporting Agentic solutions (AWS Lambda, S3, EC2, Lang Chain, Lang Graph, MCP, A2A).
• Technical expertise in LLMs, AI platforms, prompt engineering, LLM optimization, Retrieval‑Augmented Generation (RAG) architectures, and vector database technologies (Vertex AI, Postgres, Open Search, Pinecone, etc.).
• Experience in multi‑cloud environments (AWS or GCP) and working with Snowflake.
• Strong experience designing and developing complex data ecosystems leveraging next‑generation cloud technology stacks.
• Experience with real‑time data streaming, Agentic frameworks, data APIs, vector stores, and RAG architecture.
• Deep expertise in semantic layer architecture, ontology modeling, and knowledge graph design at enterprise scale.
• Proven ability to move initiatives from strategy to pilot to scaled enterprise capability.
• Excellent negotiation, influencing, and conflict resolution skills, and adept at building strong cross‑functional relationships.
• Preferred experience in the Property & Casualty insurance industry.

• Annualized base pay range: $182,000 - $273,000. Pay may vary based on performance, proficiency, and demonstrated competencies.
• Additional rewards may include short‑term or annual bonuses, long‑term incentives, and on‑the‑spot recognition.

Equal Opportunity Employer/Sex/Race/Color/Veterans/Disability/Sexual Orientation/Gender Identity or Expression/Religion/Age