Sr Data Engineer - Hybrid

Overview

Sr Staff Data Engineer - GE07DE
. We’re determined to make a difference and are proud to be an insurance company that goes well beyond coverages and policies. Joining our team means opportunities to achieve goals and help others accomplish theirs. The role focuses on implementing AI data pipelines to support AI and Agentic solutions, including pre-processing with extraction, chunking, embedding and grounding strategies to prepare data for models.

The role offers a hybrid work schedule, with in-office expectations in Hartford, CT;
Chicago, IL;
Columbus, OH; and Charlotte, NC three days a week (Tuesday through Thursday).

• Lead the implementation of AI data pipelines that bring together structured, semi-structured and unstructured data to support AI and Agentic solutions, including pre-processing with extraction, chunking, embedding and grounding strategies.
• Develop AI-driven data capabilities while ensuring compliance with industry best practices.
• Implement efficient Retrieval-Augmented Generation (RAG) architectures and integrate with enterprise data infrastructure.
• Collaborate with cross-functional teams to integrate solutions into operational processes and systems.
• Stay up to date with industry advancements in AI and apply modern technologies and methodologies.
• Design, build and maintain scalable real-time data streaming pipelines using technologies such as Apache Kafka, AWS Kinesis, Spark Streaming, or similar.
• Develop data domains and data products for various consumption archetypes including Reporting, Data Science, AI/ML, Analytics, etc.
• Ensure reliability, availability and scalability of data pipelines through monitoring, alerting and incident management.
• Apply reliability engineering practices including redundancy, fault tolerance and disaster recovery strategies.
• Collaborate with Dev Ops and infrastructure teams to ensure seamless deployment, operation and maintenance of data systems.
• Mentor junior team members and promote best practices, standards, and reusable patterns.
• Develop graph database solutions for complex data relationships supporting AI systems.
• Apply AI solutions to insurance-specific data use cases and challenges.
• Partner with architects and stakeholders to influence and implement the vision of the AI and data pipelines while safeguarding integrity and scalability.
• Develop and maintain data products and platforms that support AI/agentic solutions.

• Bachelor s or Master s degree in Computer Science, Artificial Intelligence, or a related field.
• 8+ years of hands-on data engineering experience including data solutions, SQL and No
  
  SQL, Snowflake, ETL/ELT tools, CI/CD, Big Data, Cloud technologies (AWS/GCP/Azure), Python/Spark, Data Mesh, Data Lake or Data Fabric.
• Strong programming skills in Python and familiarity with deep learning frameworks such as PyTorch or Tensor Flow.
• Experience implementing data governance practices, including data quality, lineage and data catalog capture on a large-scale data platform.
• Experience with cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).
• Strong written and verbal communication skills with the ability to explain technical concepts to stakeholders.

• Experience in multi-cloud hybrid AI solutions and AI certifications.
• Experience in the Employee Benefits industry and knowledge of NLP and computer vision technologies.
• Contributions to open-source AI projects or research in Generative AI.
• Experience building AI pipelines that integrate structured, semi-structured and unstructured data, including pre-processing with extraction, chunking, embedding and grounding strategies, semantic modeling, and data readiness for models and agentic solutions.
• Experience with vector databases, graph databases, No
  
  SQL, Document DBs (e.g., AWS Open Search, GCP Vertex AI, Neo4j, Spanner Graph, Neptune, Mongo
  
  DB, Dynamo
  
  DB).
• 3+ years of AI/ML experience, with 1+ years in data engineering focused on Generative AI technologies.
• Hands-on experience delivering production-ready enterprise-grade AI data solutions and prompt engineering for large language models.
• Experience with Retrieval-Augmented Generation (RAG) pipelines and integrating retrieval with language models.
• Experience with unstructured data processing for AI applications and scalable AI-driven data systems supporting agentic solutions (e.g., AWS Lambda, S3, EC2, Langchain, Langgraph).

The listed annualized base pay range is based on external market analysis; actual base pay may vary based on performance, proficiency and demonstrated competencies. The base pay is one component of The Hartford’s total compensation package, which may include bonuses, incentives, and recognition. Base pay range: $135,040 - $202,560.

Equal Opportunity Employer/Sex/Race/Color/Veterans/Disability/Sexual Orientation/Gender Identity or Expression/Religion/Age.

• Seniority level:
  Mid-Senior level
• Employment type:
  
  Full-time
• Job function:
  Information…