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Co","hartford-fire-ins-co",false,true,{"@context":14,"@type":15,"title":6,"description":16,"hiringOrganization":17,"datePosted":19,"validThrough":20,"jobLocationType":21,"employmentType":22,"industry":24,"skills":26,"baseSalary":118},"https:\u002F\u002Fschema.org\u002F","JobPosting","AVP, Platform Engineer - IPB05AE 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 BigQuery, 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 BigQuery, 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\u002FAPI 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. Responsibilities: 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 BigQuery, 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 ThoughtSpot, 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 BigQuery, vector search, retrieval patterns, and governed AI\u002FML platform interoperability. Build, mentor, and lead high-performing engineering teams with strong technical depth, delivery accountability, inclusive leadership, and a continuous improvement mindset. Act as a strategic advisor to senior leadership on data platform modernization, analytics enablement, AI integration opportunities, third-party data strategy, and enterprise data capability investments. Lead Third Party Data strategy, including external data sourcing, vendor data integration patterns, acquisition roadmaps, consumption models, governance, usage optimization, and business value realization. Build and mature API and data ingestion capabilities for third-party vendor data, ensuring solutions meet HIG stakeholder requirements for timeliness, quality, reliability, security, lineage, and scalability. Manage third-party data vendor relationships in partnership with business, sourcing, legal, risk, and compliance teams, including service expectations, data quality, roadmap alignment, and performance management. Translate HIG business stakeholder needs into actionable platform, data ingestion, analytics, and third-party data requirements; prioritize delivery against enterprise value, risk, and feasibility. Required Qualifications: Minimum of 12+ years of experience in data platform engineering, data architecture, data analytics, business intelligence, data warehousing, cloud data platforms, or related disciplines, with a proven track record of leadership in complex enterprise environments. Deep engineering leadership experience building and operating enterprise-scale data platforms, preferably including Snowflake, Spark, Google BigQuery, Dataproc, Dataflow, Informatica IDMC, and similar cloud-native data platform services. Strong understanding of data platform engineering practices, including platform architecture, data ingestion, orchestration, transformation, observability, performance tuning, reliability, automation, cost management, security, and operational support. Technical experience with LLMs, AI platforms, prompt engineering, LLM optimization, Retrieval-Augmented Generation (RAG) architectures and vector database technologies (Vertex AI, Postgres, OpenSearch, Pinecone etc.) Demonstrated experience leading engineering productivity improvements, platform standardization, reusable frameworks, CI\u002FCD adoption, infrastructure-as-code patterns, and modern software\u002Fdata engineering practices. • Experience with modern BI and analytics platforms such as Tableau and ThoughtSpot, including self-service analytics, governed analytics, semantic modeling, dashboard modernization, and business user enablement. Strong understanding of AI-enabled data and analytics capabilities, including Snowflake Cortex, GCP Gemini Enterprise integrations with BigQuery, conversational analytics, Chat with Data, Agentic Analytics, vector search, and AI\u002FML integration patterns. Expertise implementing or governing semantic layers, metrics layers, ontology-driven solutions, knowledge graphs, graph databases, contextual metadata, and platforms that support trusted business definitions and AI-ready enterprise knowledge models. Exceptional strategic thinking, problem-solving, systems thinking, and critical-thinking abilities, with the ability to balance near-term delivery with long-term platform strategy. Superior communication, executive presentation, and storytelling skills, with the ability to explain complex data platform, AI, analytics, and third-party data concepts to technical and non-technical audiences, including senior executives. Strong team leadership, mentoring, talent development, organizational change management, and cross-functional partnership skills. Additional experience: Experience developing third-party data strategies, vendor data integration approaches, external data acquisition models, API\u002Fdata ingestion capabilities, and business-aligned data consumption patterns. Experience with product management or platform product leadership in an enterprise setting, including roadmap development, prioritization, stakeholder engagement, OKRs, financial management, and adoption measurement. Strong knowledge of data governance, cybersecurity, privacy, compliance, data quality, lineage, metadata management, and risk management considerations for enterprise data platforms and third-party data usage. Expertise in SQL, Python, or other relevant scripting and engineering languages for data engineering, automation, analysis, and platform integration. A 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: $201,500.00 - $302,500.00 Equal Opportunity Employer\u002FSex\u002FRace\u002FColor\u002FVeterans\u002FDisability\u002FSexual Orientation\u002FGender Identity or Expression\u002FReligion\u002FAge About Us | Our Culture | What It’s Like to Work Here | Perks & Benefits Every day, a day to do right. Showing up for people isn’t just what we do. It’s who we are – and have been for more than 200 years. 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. About Us Our Culture What It’s Like to Work Here Perks & Benefits Legal Notice Accessibility Statement Producer Compensation EEO Privacy Policy California Privacy Policy Your California Privacy Choices International Privacy Policy Canadian Privacy Policy Unincorporated Areas of LA County, CA (Applicant Information) MA Applicant Notice Hartford India Prospective Personnel Privacy Notice Electronic Monitoring Policy",{"@type":18,"name":9},"Organization","2026-10-02","2027-10-02","HYBRID",[23],"PERMANENT",[25],"Insurance",[27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117],"Snowflake","Google BigQuery","Dataproc","Dataflow","Informatica IDMC","Spark","Tableau","ThoughtSpot","SQL","Python","LLMs","Prompt Engineering","Retrieval-Augmented Generation (RAG)","Vector Databases","Vertex AI","Postgres","OpenSearch","Pinecone","CI\u002FCD","Infrastructure-as-Code","API","Snowflake Cortex","GCP Gemini Enterprise","Knowledge Graphs","Graph Databases","Strategic Thinking","Problem-Solving","Systems Thinking","Critical Thinking","Communication","Executive Presentation","Storytelling","Team Leadership","Mentoring","Talent Development","Organizational Change Management","Cross-Functional Partnership","Data Platform Engineering","Data Architecture","Data Analytics","Business Intelligence","Data Warehousing","Cloud Data Platforms","Platform Architecture","Data Ingestion","Orchestration","Transformation","Observability","Performance Tuning","Reliability","Automation","Cost Management","Security","Operational Support","Engineering Productivity","Platform Standardization","Reusable Frameworks","Self-Service Analytics","Governed Analytics","Semantic Modeling","Dashboard Modernization","Business User Enablement","AI Integration","Conversational Analytics","Chat with Data","Agentic Analytics","Vector Search","AI\u002FML Integration","Semantic Layers","Metrics Layers","Ontology-Driven Solutions","Contextual Metadata","Third-Party Data Strategy","Vendor Data Integration","External Data Acquisition","Data Consumption Models","Product Management","Roadmap Development","Prioritization","Stakeholder Engagement","OKRs","Financial Management","Adoption Measurement","Data Governance","Cybersecurity","Privacy","Compliance","Data Quality","Lineage","Metadata Management","Risk Management",{"@type":119,"currency":120,"value":121},"MonetaryAmount","USD",{"@type":122,"minValue":123,"maxValue":124,"unitText":125},"QuantitativeValue",201500,302500,"YEAR",[],[],"permanent",[130],"FULL_TIME",[130],"hybrid","estimated",[135,136,137],"Short-term or annual bonuses","Long-term incentives","On-the-spot recognition",[135,136,137],"insurance",[],[],[],[],[],[],[],"# AVP, Platform Engineer - IPB05AE\n\nWe’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.\n\nAs 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 BigQuery, 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 BigQuery, 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\u002FAPI 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.\n\n## Responsibilities:\n\n- 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.\n- Lead engineering teams responsible for modern data platforms and services, including Snowflake, Spark, Google BigQuery, Dataproc, Dataflow, Informatica IDMC, and related cloud-native data engineering capabilities.\n- Improve engineering productivity by simplifying developer experience, reducing platform friction, accelerating delivery, and enabling repeatable, high-quality data product development.\n- Partner with architecture and product leaders to define data platform roadmaps, platform product strategy, service offerings, adoption plans, and measurable outcomes.\n- Lead modernization of data platform and analytics capabilities, including migration from legacy platforms, rationalization of tools, and adoption of scalable cloud-native patterns.\n- Enable enterprise BI and analytics capabilities through platforms such as Tableau and ThoughtSpot, with emphasis on trusted datasets, self-service analytics, governed data access, and reusable data products.\n- Advance next-generation analytics experiences including Chat with Data, conversational BI, Agentic Analytics, AI-assisted insight generation, and embedded intelligence across analytics workflows.\n- Develop a practical AI integration strategy for data platforms, including capabilities such as Snowflake Cortex, GCP Gemini Enterprise integrations with BigQuery, vector search, retrieval patterns, and governed AI\u002FML platform interoperability.\n- Build, mentor, and lead high-performing engineering teams with strong technical depth, delivery accountability, inclusive leadership, and a continuous improvement mindset.\n- Act as a strategic advisor to senior leadership on data platform modernization, analytics enablement, AI integration opportunities, third-party data strategy, and enterprise data capability investments.\n- Lead Third Party Data strategy, including external data sourcing, vendor data integration patterns, acquisition roadmaps, consumption models, governance, usage optimization, and business value realization.\n- Build and mature API and data ingestion capabilities for third-party vendor data, ensuring solutions meet HIG stakeholder requirements for timeliness, quality, reliability, security, lineage, and scalability.\n- Manage third-party data vendor relationships in partnership with business, sourcing, legal, risk, and compliance teams, including service expectations, data quality, roadmap alignment, and performance management.\n- Translate HIG business stakeholder needs into actionable platform, data ingestion, analytics, and third-party data requirements; prioritize delivery against enterprise value, risk, and feasibility.\n\n## Required Qualifications:\n\n- Minimum of 12+ years of experience in data platform engineering, data architecture, data analytics, business intelligence, data warehousing, cloud data platforms, or related disciplines, with a proven track record of leadership in complex enterprise environments.\n- Deep engineering leadership experience building and operating enterprise-scale data platforms, preferably including Snowflake, Spark, Google BigQuery, Dataproc, Dataflow, Informatica IDMC, and similar cloud-native data platform services.\n- Strong understanding of data platform engineering practices, including platform architecture, data ingestion, orchestration, transformation, observability, performance tuning, reliability, automation, cost management, security, and operational support.\n- Technical experience with LLMs, AI platforms, prompt engineering, LLM optimization, Retrieval-Augmented Generation (RAG) architectures and vector database technologies (Vertex AI, Postgres, OpenSearch, Pinecone etc.)\n- Demonstrated experience leading engineering productivity improvements, platform standardization, reusable frameworks, CI\u002FCD adoption, infrastructure-as-code patterns, and modern software\u002Fdata engineering practices.\n- • Experience with modern BI and analytics platforms such as Tableau and ThoughtSpot, including self-service analytics, governed analytics, semantic modeling, dashboard modernization, and business user enablement.\n- Strong understanding of AI-enabled data and analytics capabilities, including Snowflake Cortex, GCP Gemini Enterprise integrations with BigQuery, conversational analytics, Chat with Data, Agentic Analytics, vector search, and AI\u002FML integration patterns.\n- Expertise implementing or governing semantic layers, metrics layers, ontology-driven solutions, knowledge graphs, graph databases, contextual metadata, and platforms that support trusted business definitions and AI-ready enterprise knowledge models.\n- Exceptional strategic thinking, problem-solving, systems thinking, and critical-thinking abilities, with the ability to balance near-term delivery with long-term platform strategy.\n- Superior communication, executive presentation, and storytelling skills, with the ability to explain complex data platform, AI, analytics, and third-party data concepts to technical and non-technical audiences, including senior executives.\n- Strong team leadership, mentoring, talent development, organizational change management, and cross-functional partnership skills.\n\n## Additional experience:\n\n- Experience developing third-party data strategies, vendor data integration approaches, external data acquisition models, API\u002Fdata ingestion capabilities, and business-aligned data consumption patterns.\n- Experience with product management or platform product leadership in an enterprise setting, including roadmap development, prioritization, stakeholder engagement, OKRs, financial management, and adoption measurement.\n- Strong knowledge of data governance, cybersecurity, privacy, compliance, data quality, lineage, metadata management, and risk management considerations for enterprise data platforms and third-party data usage.\n- Expertise in SQL, Python, or other relevant scripting and engineering languages for data engineering, automation, analysis, and platform integration.\n- A bachelor's degree in Computer Science, Data Science, Information Systems, Engineering, Business Administration, or a related quantitative field.\n\n## Location Requirements:\n\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.\n\n## Compensation\n\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 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: $201,500.00 - $302,500.00\n\nEqual Opportunity Employer\u002FSex\u002FRace\u002FColor\u002FVeterans\u002FDisability\u002FSexual Orientation\u002FGender Identity or Expression\u002FReligion\u002FAge\n\nAbout Us | Our Culture | What It’s Like to Work Here | Perks & Benefits\n\nEvery day, a day to do right. Showing up for people isn’t just what we do. It’s who we are – and have been for more than 200 years. 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.\n\nAbout Us\n\nOur Culture\n\nWhat It’s Like to Work Here\n\nPerks & Benefits\n\nLegal Notice\n\nAccessibility Statement\n\nProducer Compensation\n\nEEO\n\nPrivacy Policy\n\nCalifornia Privacy Policy\n\nYour California Privacy Choices\n\nInternational Privacy Policy\n\nCanadian Privacy Policy\n\nUnincorporated Areas of LA County, CA (Applicant Information)\n\nMA Applicant Notice\n\nHartford India Prospective Personnel Privacy Notice\n\nElectronic Monitoring Policy",{"api":149,"sql":149,"llms":149,"ci\u002Fcd":149,"spark":149,"python":149,"tableau":149,"dataflow":149,"dataproc":149,"pinecone":149,"postgres":149,"snowflake":149,"vertex ai":149,"opensearch":149,"thoughtspot":149,"google bigquery":149,"graph databases":149,"informatica idmc":149,"knowledge graphs":149,"snowflake cortex":149,"vector databases":149,"prompt engineering":149,"gcp gemini enterprise":149,"infrastructure-as-code":149,"retrieval-augmented generation (rag)":149},4,[27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51],{"strategic thinking":149,"problem-solving":149,"systems thinking":149,"critical thinking":149,"communication":149,"executive presentation":149,"storytelling":149,"team leadership":149,"mentoring":149,"talent development":149,"organizational change management":149,"cross-functional partnership":149},[52,53,54,55,56,57,58,59,60,61,62,63],{"okrs":149,"lineage":149,"privacy":149,"security":149,"automation":149,"compliance":149,"reliability":149,"data quality":149,"cybersecurity":149,"observability":149,"orchestration":149,"vector search":149,"ai integration":149,"chat with data":149,"data analytics":149,"data ingestion":149,"metrics layers":149,"prioritization":149,"transformation":149,"cost management":149,"data governance":149,"risk management":149,"semantic layers":149,"data warehousing":149,"agentic analytics":149,"ai\u002Fml integration":149,"data architecture":149,"semantic modeling":149,"governed analytics":149,"performance tuning":149,"product management":149,"contextual metadata":149,"metadata management":149,"operational support":149,"reusable frameworks":149,"roadmap development":149,"adoption measurement":149,"cloud data platforms":149,"financial management":149,"business intelligence":149,"platform architecture":149,"self-service analytics":149,"stakeholder engagement":149,"dashboard modernization":149,"data consumption models":149,"vendor data integration":149,"business user enablement":149,"conversational analytics":149,"engineering productivity":149,"platform standardization":149,"data platform engineering":149,"external data acquisition":149,"ontology-driven solutions":149,"third-party data strategy":149},[64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117],{"detected_language_jobad":156,"required":157},"en",[158],[159],{"language":160,"level":161},"ENGLISH","C2",12,[164,165],"Information and Communications Technology Service Managers","Database and Network Professionals",[164,165],"https:\u002F\u002Fthehartford.wd5.myworkdayjobs.com\u002Fen-us\u002Fcareers_external\u002Fjob\u002Fhartford-ct\u002Favp--data-platform-engineering_r2627233",1]