Director Data and Analytics AI Engineering
Job in
Hartford, Hartford County, Connecticut, 06132, USA
Listed on 2026-10-02
Listing for:
The Hartford
Full Time
position Listed on 2026-10-02
Job specializations:
-
IT/Tech
Data Engineering, Data Science Manager, AI Engineer (Applied/Software), Data Analyst
Job Description & How to Apply Below
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.
The Hartford is seeking a Director of AI Data Engineering. Actuarial Solutions Engineering team develops and maintains cloud-based data and analytics solutions that help actuaries deliver faster, deeper, and more actionable insights for pricing, reserving, underwriting, portfolio management, and business decision making.
This role leads the delivery of governed next generation actuarial data products, semantic layers, analytic-ready datasets, AI analytic agents, dashboards, and reusable solutions designed to enable insights. Working across actuarial, analytics, data science, IT, and business teams, the leader translates use cases into scalable, production-ready Snowflake solutions and oversees data discovery, modeling, transformation, validation, governance, monitoring, and support. The role manages a complex technical team, sets priorities, resolves delivery and resource challenges, and provides expert guidance on cloud data engineering, actuarial analytics, and AI-enabled solutions.
A deep understanding of technical data capabilities coupled with a good understanding of data insights is critical to this role.
** Responsibilities** **:*
* + 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.
+ Lead Execution of a complex and large Data and Analytics portfolio.
+ Data Modernization:
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.
+ Architecture and Solution:
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.
+ AI Data Engineering leader responsible for Implementing AI data pipelines that integrate structured, semi-structured, and unstructured data to support AI and Agentic solutions.
+ Drive best practices in AI data engineering by establishing standardized processes, promoting cutting-edge technologies, and ensuring data quality and compliance across the enterprise.
+ Data and Analytics Management:
Oversee the design, development, and maintenance of data pipelines, data warehouses, data lakes and reporting systems.
+ Leadership:
Build, mentor, and lead a high-performing team including business data analysts, data engineers and release train engineers.
+ Drive efficiency and Productivity:
Identify and champion developer productivity improvements across the end-to-end data management lifecycle. This includes researching and implementing innovative solutions such as AI-driven auto-generation of data pipelines, advanced Dev Ops practices for data and automated data quality frameworks.
+ Technology Evaluation & Adoption:
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.
+ Data Governance, Stewardship and Quality:
Define and implement robust data management frameworks to ensure successful adoption of Enterprise Data Governance and Data Quality practices.
+ Budget Management:
Effectively manage the budget and financials for the portfolio.
+ 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, ML Ops and Architecture teams to influence technology, data, platform and tooling strategy.
*
* Qualifications:
*
* + 8-10 years of experience in data engineering, analytics solution delivery, actuarial analytics, or related data-intensive roles.
+ 3+ years' experience supporting actuarial, insurance, pricing, reserving, modeling, underwriting, portfolio management,…
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