Senior Staff AI Data Engineer - Hybrid

The Hartford

Hybrid

Quick summary

Work type
Hybrid
Location
Hartford, CTCharlotte, NCColumbus, OHChicago, IL
Salary
$135,040–$202,560 / yr
Posted
4 days ago

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $202k
This role $169k
$122k most similar roles pay here $258k

This role pays less than 65% of similar roles. Most pay $158,212–$245,112 — the shaded band above. At the midpoint, this role pays about $169k versus about $202k for comparable roles.

Based on 240 similar postings.

Employer

About The Hartford

The Hartford is a leading provider of property and casualty insurance, group benefits, and mutual funds, serving businesses and individuals across the United States. Industry: Insurance & Financial Services

The Hartford currently has 61 open roles on FindRole.

Listed pay typically runs $131,600–$191,400 across 61 roles with salary data.

Most-posted roles

View all roles at The Hartford

At a glance

TL;DR · Senior Staff AI Data Engineer - Hybrid

As a Senior Staff Data Engineer at our innovative company, you will lead the development of advanced AI data pipelines and systems, integrating structured, semi-structured, and unstructured data to support cutting-edge agentic solutions. Your daily tasks include designing scalable batch and streaming data pipelines, implementing Retrieval-Augmented Generation (RAG) architectures, and ensuring the reliability and scalability of these systems through robust monitoring and incident management practices. You will work with modern cloud platforms like AWS, GCP, Azure, and Snowflake, using Python for data engineering tasks, while also mentoring junior engineers and promoting best practices within your team. This role demands expertise in AI-driven data solutions, ETL/ELT architecture, and a deep understanding of SQL and large-scale data processing systems, with an emphasis on delivering resilient, governed, and cost-efficient platforms at scale.

What you'll do

  • Lead implementation of AI data pipelines integrating various data types.
  • Develop and optimize Retrieval-Augmented Generation (RAG) architectures.
  • Design scalable batch and streaming data pipelines for performance.
  • Ensure reliability, availability, and scalability of data pipelines through monitoring.
  • Implement fault tolerance, redundancy, and disaster recovery practices.
  • Drive engineering discipline across data platforms with focus on observability.

What we're looking for

  • 8+ years of data engineering experience with expertise in SQL, data modeling, and large-scale data processing systems.
  • Proven experience designing and optimizing ETL/ELT pipelines and orchestration frameworks in enterprise environments.
  • Hands-on experience implementing production-ready, enterprise-grade GenAI data solutions.
  • Experience operationalizing RAG pipelines including retrieval, chunking, embedding, and grounding techniques.
  • Strong programming skills in Python and hands-on experience with cloud ecosystems (AWS, GCP, Azure).
  • Proficiency in building AI data pipelines integrating structured and unstructured data with preprocessing techniques.
  • Experience implementing data governance practices, including data quality, lineage, and cataloging at scale.

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