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Principal Reliability Engineer - EDS

Remote / Online - Candidates ideally in
Hartford, Hartford County, Connecticut, 06112, USA
Listing for: The Hartford
Part Time, Remote/Work from Home position
Listed on 2026-02-15
Job specializations:
  • IT/Tech
    Cloud Computing, Data Engineer, SRE/Site Reliability, Systems Engineer
Salary/Wage Range or Industry Benchmark: 100000 - 125000 USD Yearly USD 100000.00 125000.00 YEAR
Job Description & How to Apply Below

Overview

Principal Reliability Engineering - IE06JE

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.

The Enterprise Data Services (EDS) organization is seeking a Principal Reliability Engineer (Principal RE) to serve as the senior technical authority responsible for the reliability, resilience, availability, and performance of all data platforms, cloud infrastructure, data products, and data pipelines across the enterprise data organization. This role sets the strategic vision for Reliability Engineering within EDS and leads the definition, implementation, and continuous evolution of RE practices, tooling, automation, observability frameworks, and AIOps/AI‑driven operations.

As the Principal RE, you will influence architectural direction, lead large‑scale, cross‑organizational technical initiatives, and drive a culture of engineering excellence, automation‑first operations, and proactive reliability improvement. You will partner closely with platform engineering, data engineering, security, architecture, and product teams to embed RE principles into every stage of the data product lifecycle.

This role can have a Hybrid or Remote work schedule. Candidates who live near one of our office locations will have the expectation of working in an office 3 days a week (Tuesday through Thursday). Candidates who do not live near an office will have a remote work arrangement, with the expectation of coming into an office as business needs arise.

Must be eligible to work in the US without company sponsorship.

Key Responsibilities Enterprise Reliability Strategy & Leadership
  • Work closely with the AVP, RE & Production Support, EDS defining the Reliability Engineering strategy for data platforms, data cloud environments, and data products.
  • Establish long‑term RE roadmaps, target operating models, and architectural patterns that scale with organizational growth.
  • Serve as the highest‑level technical escalation point for systemic reliability issues, influencing executive stakeholders and engineering leaders.
Platform & Cloud Reliability (AWS, GCP, Snowflake, EMR, Hadoop, ETL/ELT)
  • Leverage Enterprise provided standards and building blocks to Architect and evolve highly reliable, performant, and cost‑efficient cloud‑based platforms across AWS and GCP for all EDS services.
  • Influence and work directly with Platform Solution Architecture on new product enablement, hyper automation (end to end blueprint automation).
  • Oversee reliability controls and fail‑safe patterns for Snowflake, EMR, Hadoop/Spark clusters, container platforms (e.g., Kubernetes), and mission‑critical data systems.
  • Lead the creation and enforcement of SLO/SLI frameworks that span the entire data lifecycle.
AI‑Enabled Operations, AIOps & Intelligent Automation
  • Develop and implement AI‑driven automation for anomaly detection, alert correlation, autonomous remediation, and predictive capacity management.
  • Leverage LLMs, prompt engineering, and cloud‑native AI services (AWS Bedrock, Sage Maker, Vertex AI) to build intelligent runbooks, advanced troubleshooting agents, and generative‑AI‑enabled operational tooling.
  • Champion the adoption of machine learning–based observability and reliability analytics.
End‑to‑End Observability & Operational Excellence
  • Adopt and architect enterprise‑wide data observability frameworks—including logging, metrics, tracing, distributed profiling, and event pipelines—for all data platforms and pipelines.
  • Establish gold‑standard incident response patterns, post‑incident reviews, and continuous improvement processes.
  • Drive elimination of toil across EDS, focusing on self‑healing systems, proactive detection, and autonomous operations.
Data Pipeline & Data Product Reliability
  • Define RE best practices for modern data products, governed data pipelines, real‑time/streaming systems, and operational analytics platforms.
  • Ensure data quality, data timeliness, and SLAs for data products through automated checks, lineage‑informed…
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