AVP, Data Engineering

$176,000 - $264,000/Yr

The Hartford - Hartford, CT

posted 2 months ago

Full-time - Senior
Hartford, CT
10,001+ employees
Insurance Carriers and Related Activities

About the position

The Hartford is seeking a highly skilled and experienced Data and Technology leader for the position of Assistant Vice President (AVP) of Data Engineering. This role is pivotal in shaping the future of data management within the company, focusing on the design, building, and maintenance of scalable data pipelines and infrastructure that align with the company's strategic objectives. The ideal candidate will possess a strong background in Real Time data streaming, expertise in graph knowledge bases, and familiarity with AI Retrieval-Augmented Generation (RAG) architectures. The AVP will lead a team of data engineers, providing technical guidance and mentoring while collaborating with cross-functional teams to ensure that data engineering initiatives are aligned with business goals. In this role, the AVP will be responsible for developing and implementing strategies for data infrastructure that support Real Time data streaming, graph databases, and AI-powered applications. The position requires a thought leader who can drive positive change and simplification while improving delivery speed. The AVP will also design and implement self-serve data platforms that empower business users to access and analyze data independently, thereby enabling data democratization. Additionally, the AVP will collaborate with AI and data science teams to support AI use cases, ensuring that data pipelines are optimized for AI/ML workflows. The role involves architecting and maintaining graph databases to support complex data relationships and queries, as well as developing strategies for mining and analyzing unstructured data. The AVP will also be responsible for implementing data governance practices, ensuring the reliability and scalability of data pipelines, and working closely with DevOps and infrastructure teams to maintain data systems. This position offers a hybrid work arrangement, requiring in-office presence three days a week in one of the specified locations.

Responsibilities

  • Lead and manage a team of data engineers, providing technical guidance, mentoring, and career development opportunities.
  • Collaborate with cross-functional teams, including data science, product development, and IT, to align data engineering initiatives with business goals.
  • Develop and implement strategies for data infrastructure that support Real Time data streaming, graph databases, and AI-powered applications.
  • Design and implement self-serve data platforms that empower business users to access, analyze, and leverage data without heavy reliance on engineering teams.
  • Collaborate with AI and data science teams to develop and support AI use cases, ensuring data pipelines and infrastructure are tailored to meet the demands of AI/ML workflows.
  • Design, build, and maintain scalable and robust Real Time data streaming pipelines using technologies such as Apache Kafka, AWS Kinesis, Spark streaming or similar.
  • Architect, implement, and maintain graph databases to support complex data relationships and queries.
  • Collaborate with data scientists and AI engineers to develop and deploy Retrieval-Augmented Generation (RAG) systems that enhance AI-driven applications.
  • Develop and implement strategies for mining and analyzing unstructured data to extract valuable insights.
  • Implement data governance practices, ensuring data quality, lineage, and catalog capture on a large-scale data platform.
  • Ensure the reliability, availability, and scalability of data pipelines and systems through effective monitoring, alerting, and incident management.

Requirements

  • 15+ years of experience in data engineering, design and development of large-scale data ecosystems and delivery experience.
  • 10+ years of technical leadership experience.
  • Mastery level Data Engineering and Architecture skills with a deep understanding of data architecture patterns, data warehouse, integration, data lake, data domains, data products, BI, and cloud technology capabilities.
  • Hands-on expertise in Dynamo DB, Kinesis, AWS EC2, Python, Spark, and Scala with Spark streaming experience.
  • Strong experience with design and development of complex data ecosystems leveraging next generation of cloud technology stack across AWS Cloud, PySpark, and Snowflake.
  • Extensive experience on No SQL databases design and optimizations for API consumptions.
  • Strong experience with BI tools like Tableau, ThoughtSpot or similar.
  • In-depth knowledge of Data management strategies, principles, and practices including experience with framework for data quality, data governance, data domains, data products, stewardship, and metadata management.

Nice-to-haves

  • Experience in the Omni Channel Customer insights and Property & Casualty insurance industry is preferred.
  • Agile experience/mindset, portfolio delivery experience, engaging in the full lifecycle experience.

Benefits

  • Short-term or annual bonuses
  • Long-term incentives
  • On-the-spot recognition
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