Senior Platform Engineer - Cloud Data & Automation Leader

The Hartford

Chicago (IL)

On-site

USD 137,000 - 206,000

Full time

2 days ago
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Job summary

The Hartford's Data Analytics and AI Office (DAIO) – and Data Platform Services (DPS) Team is seeking a Senior Staff Platform Engineer to design cloud data platforms, define target architectures, and drive adoption across analytics teams.

This role combines hands-on IaC work with strategic leadership, evaluating new technologies, building scalable platforms (AWS, GCP, Snowflake, Tableau, ThoughtSpot) and collaborating with internal customers on batch/real-time pipelines and AI initiatives.

Qualifications

  • Bachelor’s degree (or foreign equivalent) in CS, CE, or related field.
  • 6+ years in cloud computing, data delivery, analytics, or equivalent.
  • 3+ years providing architectural guidance to developers or platform admins.
  • 2+ years implementing solutions in AWS and GCP.
  • Ability to learn quickly and contribute within 6–12 months.
  • Experience with agile/scrum methodologies and strong communication.

Responsibilities

  • Analyze industry trends in cloud computing and data platform technologies.
  • Design target state architectures and define roadmaps.
  • Collaborate with internal customers to guide product usage for analytics pipelines.
  • Lead hands-on IaC development and evaluate new technologies.
  • Support adoption through technical roadshows and demos.

Skills

Cloud computing
Data platforms
Architectural guidance
Agile/Scrum
Communication
DevOps
IaC

Education

Bachelor’s degree in CS/CE or related field

Tools

AWS
GCP
Snowflake
Tableau
ThoughtSpot
PySpark
Terraform

Job description

The Hartford's Data Analytics and AI Office (DAIO) – and Data Platform Services (DPS) Team is seeking a Senior Staff Platform Engineer to design cloud data platforms, define target architectures, and drive adoption across analytics teams.

This role combines hands-on IaC work with strategic leadership, evaluating new technologies, building scalable platforms (AWS, GCP, Snowflake, Tableau, ThoughtSpot) and collaborating with internal customers on batch/real-time pipelines and AI initiatives.

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