AVP, Data Platform Engineering

AVP, Platform Engineer - IPB
05AE
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. As the AVP Data Platform Engineering, you will be a senior engineering leader responsible for defining, building, and operating enterprise-grade data platforms, analytics capabilities, and third-party data ingestion services that enable scalable, reliable, secure, and cost-effective data and AI outcomes across HIG.

This role will lead engineering teams accountable for modern cloud data platforms such as Snowflake, Google Big Query, Dataproc, Dataflow, and Informatica IDMC, while also enabling enterprise insights and self-service analytics capabilities through business intelligence platforms. The leader in this role will be responsible for driving strong engineering practices, platform modernization, developer productivity, operational reliability, and product-oriented delivery for data platform services.

The role requires a strong understanding of how AI capabilities integrate into modern data platforms, including Snowflake Cortex, GCP Gemini Enterprise integrations with Big Query, conversational analytics, Chat with Data, and emerging Agentic Analytics patterns. This leader will also provide the foundations of enterprise capabilities around semantic layers, ontology, knowledge graphs, and related platforms that enable trusted, contextual, reusable, and business-aligned analytics experiences.

In addition, this role will provide leadership for Third Party Data strategy, including vendor data acquisition, data/API ingestion capability development, platform integration, business stakeholder engagement, and delivery of external data capabilities that meet HIG business requirements. The role requires close partnership across Enterprise Data Services, AI & Analytics, Architecture, Cybersecurity, Data Governance, business stakeholders, and external vendors to ensure that platform and third-party data solutions are secure, governed, scalable, and aligned to enterprise priorities.

We're devoted to finding innovative ways to serve our customers, communities and employees - continually asking ourselves what more we can do. Is our policy language as simple and inclusive as it can be? Can we better help businesses navigate our ever-changing world? What else can we do to destigmatize mental health in the workplace? Can we make our communities more equitable?

That we can rise to the challenge of these questions is due in no small part to our company values that our employees have shaped and defined. And while how we contribute looks different for each of us, it's these values that drive all of us to do more and to do better every day.

Define and execute a multi-year engineering strategy for enterprise data platforms, BI enablement, self-service analytics, AI-enabled analytics, and Third Party Data capabilities aligned with HIG business priorities. Lead engineering teams responsible for modern data platforms and services, including Snowflake, Spark, Google Big Query, Dataproc, Dataflow, Informatica IDMC, and related cloud-native data engineering capabilities. Improve engineering productivity by simplifying developer experience, reducing platform friction, accelerating delivery, and enabling repeatable, high-quality data product development.

Partner with architecture and product leaders to define data platform roadmaps, platform product strategy, service offerings, adoption plans, and measurable outcomes. Lead modernization of data platform and analytics capabilities, including migration from legacy platforms, rationalization of tools, and adoption of scalable cloud-native patterns. Enable enterprise BI and analytics capabilities through platforms such as Tableau and Thought Spot, with emphasis on trusted datasets, self-service analytics, governed data access, and reusable data products.

Advance next-generation analytics experiences including Chat with Data, conversational BI, Agentic Analytics, AI-assisted insight generation, and embedded intelligence across analytics workflows. Develop a practical AI integration strategy for data platforms, including capabilities such as Snowflake Cortex, GCP Gemini Enterprise integrations with Big Query, vector search, retrieval patterns, and governed AI/ML platform…