{"id":1353865,"url":"https://alion.io/job/the-hartford-avp-data-platform-engineering","title":"AVP, Data Platform Engineering","company":{"id":1760358,"name":"The Hartford","domain":"thehartford.com","url":"https://alion.io/company/thehartford-com","size_band":"501-1000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"B","score":76,"open_postings":23,"ghost_share":0,"stale_share":0.957,"repost_share":0,"time_to_fill_p50_days":24,"computed_at":"2026-10-02T05:45:00Z"}},"role":"DevOps","role_family":"DevOps","seniority":"head","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Hartford, United States","Charlotte, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":201500,"max":302500,"currency":"USD","period":"year","gross":null,"usd_annual":302500},"salary_estimate":null,"experience_years_min":12,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"BigQuery","optional":false},{"name":"CI/CD","optional":false},{"name":"Cortex","optional":false},{"name":"Gemini","optional":false},{"name":"Google BigQuery","optional":false},{"name":"GraphRAG","optional":false},{"name":"Informatica","optional":false},{"name":"Knowledge Graph","optional":false},{"name":"Platform Engineering","optional":false},{"name":"RAG","optional":false},{"name":"Semantic Search","optional":false},{"name":"Semantic Search","optional":false},{"name":"Snowflake","optional":false},{"name":"Tableau","optional":false},{"name":"Prometheus","optional":true}],"status":"live","first_seen_at":"2026-09-27T21:19:15Z","employer_posted_date":"2026-09-27","last_verified_at":"2026-10-02T14:04:22Z","board_verified":true,"closed_at":null,"days_open":5,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":5},"description":"AVP, Platform Engineer - IPB05AEWe’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.\nAs the AVP, Data Platform Engineering, you will provide strategic and technical leadership for enterprise data platforms, semantic and knowledge platforms, analytics capabilities, data integration services, AI-enabled data solutions, and Third-Party Data enablement across The Hartford.\nThis role is responsible for leading teams that build, modernize, and operate scalable, secure, and reliable data and knowledge platforms that enable analytics, AI, business intelligence, graph-based architectures, and enterprise consumption of internal and external data assets. The successful candidate will drive platform strategy, engineering excellence, technology transformation, operational effectiveness, and the advancement of semantic and knowledge capabilities that support enterprise priorities and business outcomes.\nThe ideal candidate combines deep engineering leadership experience with expertise in enterprise data platforms, graph databases, semantic layers, ontologies, knowledge graphs, and AI-ready data architectures. This leader will influence technical and business stakeholders, accelerate modern data and AI capabilities, expand Third-Party Data services, and develop high-performing teams that deliver measurable business value.\nResponsibilities\nEngineering Leadership & Strategy\nDefine and execute a multi-year strategy for enterprise data platforms, semantic and knowledge platforms, analytics enablement, AI-ready data capabilities, data integration services, Third-Party Data capabilities, and platform modernization aligned to business and technology priorities.\nServe as the senior technical leader for enterprise data and knowledge platforms, providing architecture guidance, engineering direction, and technology decision-making across data, analytics, AI-enabled capabilities, graph technologies, semantic platforms, and external data ecosystems.\nServe as the executive technology leader for enterprise semantic and knowledge platforms, including graph databases, semantic layers, ontology services, metadata platforms, and knowledge graph capabilities, establishing roadmaps, adoption strategies, and long-term investment plans.\nPartner with Architecture, Product, AI & Analytics, Cybersecurity, Data Governance, Procurement, Risk, Legal, and business leaders to define platform roadmaps, service offerings, adoption plans, and measurable outcomes.\nLead organizational transformation initiatives that improve engineering maturity, operational effectiveness, delivery speed, and team capabilities.\nBuild, mentor, and develop high-performing engineering leaders and teams through coaching, talent development, succession planning, and organizational design.\nFoster a culture of innovation, accountability, technical excellence, collaboration, and continuous improvement.\nServe as a trusted advisor to senior technology and business leaders on platform modernization, semantic technologies, AI enablement, Third-Party Data capabilities, emerging technologies, and enterprise data investments.\nData Platform Engineering\nLead engineering teams responsible for enterprise data, semantic, and knowledge platforms, including Snowflake, Spark, Google BigQuery, Dataproc, Dataflow, graph databases, metadata platforms, Informatica IDMC, and related cloud-native engineering capabilities.\nDrive modernization of enterprise data and knowledge platform capabilities through cloud adoption, platform rationalization, legacy migration, automation, and scalable engineering practices.\nOwn the engineering lifecycle of graph database platforms, semantic layers, ontology services, and knowledge graph technologies, including architecture, scalability, performance optimization, reliability engineering, observability, security, and operational support.\nEstablish engineering standards and operating models for graph databases, semantic technologies, metadata services, business vocabularies, entity relationship management, and AI-ready information architectures.\nEstablish engineering standards and best practices for platform architecture, data ingestion, orchestration, transformation, observability, reliability, performance optimization, security, automation, and cost management.\nImprove engineering productivity through platform standardization, self-service capabilities, reusable engineering patterns, CI/CD adoption, infrastructure-as-code practices, and modern software engineering approaches.\nEnsure enterprise data, semantic, and knowledge platforms are designed and operated for scalability, resilience, security, compliance, and operational excellence.\nLead the operationalization of new and evolving platform capabilities and services across the enterprise data ecosystem.\nSemantic, Graph & Knowledge Platform Engineering\nLead the strategy, engineering, modernization, and operational management of enterprise graph database platforms, semantic technologies, ontology services, knowledge graphs, and metadata-driven capabilities.\nOwn the scalability, reliability, performance optimization, observability, security, and operational excellence of platforms supporting enterprise knowledge models and semantic architectures.\nEstablish engineering standards and best practices for graph databases, semantic layers, ontology frameworks, metadata management, relationship modeling, entity resolution, and trusted business definitions.\nLead teams responsible for designing, operating, and continuously improving semantic and knowledge platforms that support business intelligence, analytics, AI enablement, and enterprise data consumption.\nPartner with Architecture, Data Governance, AI, Analytics, and business stakeholders to define enterprise semantic strategies, knowledge models, metadata standards, and platform roadmaps.\nDrive adoption of graph-based and ontology-driven technologies to improve data discoverability, business context, knowledge management, and AI-readiness across the enterprise.\nEnsure enterprise semantic and knowledge platforms are engineered for scalability, governance, interoperability, compliance, and long-term sustainability.\nEvaluate and guide implementation of graph database technologies, semantic search capabilities, contextual metadata services, GraphRAG architectures, vector search technologies, and emerging knowledge platform capabilities.\nAnalytics & Business Intelligence\nEnable enterprise analytics and business intelligence capabilities through platforms such as Tableau and ThoughtSpot, emphasizing trusted datasets, reusable data products, governed data access, semantic modeling, and self-service analytics.\nPartner with analytics and business teams to deliver scalable, trusted, and business-aligned insights.\nAdvance next-generation analytics experiences including conversational analytics, Chat with Data, AI-assisted insight generation, embedded intelligence, and Agentic Analytics capabilities.\nDrive modernization of analytics capabilities to improve data accessibility, business adoption, governance, performance, and user experience.\nAI-Ready Data Foundations\nLead the engineering strategy and platform capabilities that support AI-ready enterprise data and knowledge platforms.\nBuild, scale, and operationalize enterprise semantic platforms supporting ontology frameworks, semantic layers, graph databases, knowledge graphs, contextual metadata services, business vocabularies, and trusted enterprise knowledge models.\nLead engineering teams responsible for the performance, optimization, administration, scalability, governance, and operational management of graph databases and semantic technologies supporting AI-enabled enterprise capabilities.\nDefine and evolve enterprise capabilities supporting semantic search, relationship modeling, entity resolution, knowledge retrieval, GraphRAG architectures, vector search, and AI-driven business discovery.\nPartner with AI and analytics leaders to ensure enterprise platforms support emerging AI use cases and future AI initiatives.\nSupport integration of technologies and capabilities such as Snowflake Cortex, Gemini Enterprise integrations with BigQuery, vector search technologies, Retrieval-Augmented Generation (RAG) architectures, GraphRAG capabilities, and AI/ML platform interoperability.\nEnsure AI-enabling data capabilities are governed, scalable, secure, reusable, and aligned with enterprise architecture and governance standards.\nRequired Qualifications\n12+ years of experience in data platform engineering, data architecture, semantic technologies, knowledge platforms, cloud data platforms, analytics technologies, infrastructure engineering, or related disciplines with a proven track record of leadership in complex enterprise environments.\nDeep engineering leadership experience building, operating, and modernizing enterprise-scale data, semantic, and knowledge platforms.\nStrong understanding of data platform engineering practices, including platform architecture, ingestion, orchestration, transformation, observability, reliability, automation, performance tuning, cost management, security, and operational support.\nStrong engineering and platform leadership experience supporting graph databases, semantic technologies, ontology-driven solutions, knowledge graphs, metadata platforms, metrics layers, or related enterprise knowledge technologies.\nDemonstrated experience leading teams responsible for the architecture, scalability, optimization, reliability, and operational support of graph database platforms, semantic layers, ontology services, and AI-ready knowledge architectures.\nDeep understanding of semantic technologies, contextual metadata management, entity modeling, relationship modeling, business vocabularies, knowledge representation, and trusted business definitions.\nHands-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.\nDemonstrated success leading platform modernization, cloud transformation, engineering maturity improvements, and organizational change initiatives.\nExperience leading enterprise Third-Party Data capabilities, including external data acquisition, vendor-enabled data services, onboarding frameworks, governance, compliance, and operational management.\nStrong understanding of AI-enabled data ecosystems, including GraphRAG, vector databases, vector search technologies, Retrieval-Augmented Generation (RAG), Snowflake Cortex, Gemini Enterprise integrations, Agentic AI capabilities, and AI/ML integration patterns.\nExceptional strategic thinking, systems thinking, and problem-solving capabilities with the ability to balance near-term execution and long-term platform strategy.\nStrong executive communication, presentation, and storytelling skills with the ability to explain complex technical concepts to both technical and non-technical audiences.\nProven ability to build, mentor, and develop high-performing teams while leading through organizational change and transformation.\nExperience influencing stakeholders and driving results in highly matrixed organizations.\nLocation Requirements:\nThis 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.\nCompensation\nThe 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...","description_format":"text","description_chars":12620,"description_truncated":true,"requirements":{"experience_years_min":12,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":["Annual bonuses"],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Financial Services","Property & Casualty Insurance","Pet Food, Supplies & Care"],"lifecycle":[{"event":"open","at":"2026-09-27T21:19:15Z"}],"liveness":{"score":62,"band":"ok","label":"Likely open","p_open":1,"p_active":0.624,"p_room":1,"age_days":4,"expected_fill_days":24,"reasons":["conf:32","stale_co","velocity","win:early","comp:brand"],"computed_at":"2026-10-02T05:45:00Z"},"pay":{"stated_usd_annual":302500,"is_top_pay":true},"html_url":"https://alion.io/job/the-hartford-avp-data-platform-engineering","json_url":"https://alion.io/job/the-hartford-avp-data-platform-engineering.json","meta":{"generated_at":"2026-10-03T04:26:25Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":4717,"day_limit":5000,"remaining_today":283,"minute_limit":60,"resets_at":"2026-10-04T00:00:00Z"}}}