AVP, Data Platform Engineering

Analytics & Business Intelligence

AI-Ready Data Foundations

Data Integration & Third-Party Data Enablement

Global & Matrixed Leadership

Required Qualifications

• 12+ years of experience in data platform engineering, data architecture, cloud data platforms, analytics technologies, infrastructure engineering, or related disciplines, with a proven track record of leadership in complex enterprise environments.
• Deep engineering leadership experience building, operating, and modernizing enterprise-scale data platforms, including Snowflake, Spark, Google BigQuery, Dataproc, Dataflow, Informatica IDMC, and comparable cloud-native technologies.
• Strong understanding of data platform engineering practices, including platform architecture, ingestion, orchestration, transformation, observability, reliability, automation, performance tuning, cost management, security, and operational support.
• Hands-on engineering background with the technical depth to guide architecture decisions, evaluate engineering tradeoffs, influence technology strategy, and provide credible leadership to architects and engineers.
• Demonstrated success leading platform modernization, cloud transformation, engineering maturity improvements, and organizational change initiatives.
• Experience leading enterprise Third-Party Data capabilities, including external data acquisition, vendor-enabled data services, onboarding frameworks, governance, compliance, and operational management.
• Demonstrated success partnering with business stakeholders, strategic vendors, and cross-functional teams to deliver solutions leveraging external data assets and services.
• Strong understanding of Third-Party Data lifecycle management, including acquisition, integration, governance, quality, lineage, compliance, risk management, and enterprise consumption patterns.
• Experience with modern analytics and business intelligence platforms such as Tableau and ThoughtSpot, including self-service analytics, semantic modeling, dashboard modernization, and business user enablement.
• Strong understanding of AI-enabled data ecosystems, including Snowflake Cortex, Gemini Enterprise integrations with BigQuery, conversational analytics, Chat with Data, Agentic Analytics, vector search technologies, AI/ML integration patterns, and Retrieval-Augmented Generation (RAG) architectures.
• Experience supporting or implementing semantic layers, ontology-driven solutions, knowledge graphs, contextual metadata, metrics layers, and AI-ready enterprise knowledge models.
• Exceptional strategic thinking, systems thinking, and problem-solving capabilities with the ability to balance near-term execution and long-term platform strategy.
• Strong executive communication, presentation, and storytelling skills with the ability to explain complex technical concepts to both technical and non-technical audiences.
• Proven ability to build, mentor, and develop high-performing teams while leading through organizational change and transformation.
• Experience influencing stakeholders and driving results in highly matrixed organizations.

Preferred Qualifications

• Experience with Google Cloud Platform and cloud-native data engineering ecosystems.
• Experience leading Snowflake modernization, migration, optimization, or platform strategy initiatives.
• Experience supporting semantic layer, ontology, knowledge graph, metadata, or AI-ready data platform initiatives.
• Experience building or modernizing enterprise Third-Party Data platforms, acquisition frameworks, vendor data ecosystems, and external data enablement capabilities.
• Experience with enterprise data integration, API enablement, Informatica, master data management, and large-scale data ecosystems.
• Experience leading distributed or global engineering teams.
• Strong knowledge of data governance, cybersecurity, privacy, compliance, data quality, lineage, metadata management, and risk management practices.
• Experience within insurance, financial services, or other highly regulated industries.
• Bachelor's degree in Computer Science, Data Science, Information Systems, Engineering, Business Administration, or a related quantitative field.

​Location Requirements

• This role can have a Hybrid or Remote work arrangement. Candidates who live near our Hartford, CT or Charlotte offices will have the expectation of working in an office 3 days a week (Tuesday through Thursday). Candidates who do not live near an office should maintain their current work arrangement with the expectation of coming into the office as business needs arise.

Compensation

• The listed annualized base pay range is primarily based on analysis of similar positions in the external market. Actual base pay could vary and may be above or below the listed range based on factors including but not limited to performance, proficiency and demonstration of competencies required for the role. The base pay is just one component of The Hartford’s total compensation package for employees. Other rewards may include short-term or annual bonuses, long-term incentives, and on-the-spot recognition. The annualized base pay range for this role is:
• Equal Opportunity Employer/Sex/Race/Color/Veterans/Disability/Sexual Orientation/Gender Identity or Expression/Religion/Age