AVP Data Engineering & Analytics, Employee Benefits

The Hartford•Hartford, CT

8h•Hybrid

About The Position

The Employee Benefits (EB) organization is committed to modernizing its data and reporting infrastructure to enhance analytics, deepen insights, and improve customer experiences. As the AVP, EBBI and Analytics, you will be a key leader responsible for defining, delivering, and scaling actuarial data assets, reporting platforms, and analytical capabilities that support both Actuarial functions and strategic decision-making across the EB portfolio. Reporting to the Chief Actuary, Employee Benefits, this role leads the EB business intelligence team, overseeing actuarial data assets, employer reporting, and business intelligence to ensure data accuracy, timeliness, accessibility, and self-service capabilities. Success requires a blend of execution discipline, innovative thinking, business partnership, customer centricity, and data/analytics expertise. This leader will balance near-term delivery with long-term modernization, maintaining strong controls and focusing on business impact. This position offers a unique opportunity to influence how actuarial and business teams use data, improve critical decision-making tools and analytics, and significantly enhance the employer customer experience. If you are motivated by leading impactful work, developing innovative solutions, and advancing a data-driven culture, this role provides a strong platform for making a lasting difference.

Requirements

10+ years of experience in actuarial, insurance analytics, or data-focused roles, with significant leadership responsibility.
Solid understanding of group insurance products, actuarial pricing or valuation, and the data required to support them.
Demonstrated experience leading complex, cross-functional, externally-facing initiatives.
Proven ability to operate effectively in a highly matrixed organization and influence without direct authority.
Exceptional communication skills with the ability to engage technical experts and senior executives alike.
Strong command of actuarial data, reporting, and BI concepts, including data quality, controls, automation, and self-service enablement.
Bachelor’s degree required.
Must be eligible to work in the US without company sponsorship.

Responsibilities

Continually refine and execute on the actuarial data strategy aligned to EB pricing and valuation, and in support of EB’s growth objectives.
Execute on the migration of the actuarial data assets to the cloud while also rationalizing and simplifying into a consolidated asset that will support more granular and expanded analytics and reduce reconciliation.
Partner closely with Data Science and the actuarial team to continually bring together new innovative sources of data to find new insights to drive a competitive advantage.
As part of underwriting transformation, be a key player in reimagining the process and tooling needed for the future.
Continue to own and enhance analytics within EBDash, which is EB’s central BI portal for largely all functions across the business.
Support the BI activities across the various agile teams in EB’s invest and maintenance portfolio partnering closely with the EB strategic data team.
Drive modernization of legacy reporting and BI platforms; Partner with the Enterprise Data & Analytics Office and EB’s Strategic Data team to align on platforms, tools, standards, and sequencing of investments, reducing technical debt while enabling scalable, reusable, and modern analytics capabilities.
Develop and ensure on-time, accurate delivery of all ongoing employer reporting commitments.
Be the business owner to transform the employer reporting and insights platform experience and organization with the migration to Microstrategy.
Deliver major roadmap commitments, including data platform migrations, reporting re-platforming, and new insight dashboards.
Act as a trusted partner to Actuarial, the Transformation Office, Underwriting, Finance, Sales & RM, and the Enterprise Data Office.
Translate complex actuarial and data topics into clear insights, tradeoffs, and recommendations for senior leadership.
Influence prioritization decisions by articulating clear value cases, risks, and dependencies.
Lead and develop a high-performing team of data engineers, BI developers and reporting leaders, fostering accountability, strong technical depth, and business orientation.
Build strong succession and development pathways, balancing specialist expertise with broader enterprise perspective.
Role-model disciplined execution, constructive challenge, and collaborative leadership in a matrixed environment.