Data Engineer

HTD Talent • Full-time • Charlotte Metro, US • 1d ago

Data Engineering Specialist (Hybrid) – Claims Analytics

About the Company

Our client is a mid‑sized U.S. property and casualty insurer with nearly a century of consistent financial performance. The organization has been recognized among the “Best Midsize Employers” and has earned a Great Place to Work® certification multiple years in a row. Employees are encouraged to bring their authentic selves, diverse experiences and unique perspectives to a collaborative, high‑performing team that helps customers mitigate loss and recover after insured events.

Role Overview

The Data Engineering Specialist will join the Claims Analytics group within the Information Management team. This group is responsible for data engineering, machine‑learning engineering, analytics and reporting in support of the claims business. The position will be based at hybrid office locations in North Carolina and New Jersey; candidates in New Jersey will work from a nearby site while a new headquarters is under construction. The role demands hands‑on expertise and a track record of successfully delivering data‑driven projects.

Responsibilities

Design, develop and maintain both new and existing data applications and pipelines.
Work with leads to translate high‑level data flow architectures into detailed implementation designs.
Provide technical guidance to the team and lead the implementation of complex data solutions.
Conduct code reviews, testing, deployment and documentation for data‑engineering and integration applications.
Optimize schemas and fine‑tune SQL and ETL pipelines across data lake and warehouse environments.
Mentor junior engineers and collaborate with product owners, program managers and scrum masters in a scaled agile environment.
Monitor data‑pipeline health, create contingency plans for failures and support production issues.
Maintain thorough documentation to support downstream integrations and business partners.

Required Qualifications

Five to seven years of experience in data warehousing, integration or engineering.
Proven ability to collaborate across departments and with external partners.
Expert proficiency in Python, SQL and Spark; strong experience with at least one major cloud platform (Azure, AWS or GCP).
Deep knowledge of Databricks and Delta Lake, and experience building enterprise‑scale data platforms for advanced analytics and machine learning.
Experience with streaming/event‑driven architectures such as Kafka or Kinesis; strong understanding of data security and access control in regulated environments.
Advanced SQL skills, the ability to debug complex issues, and familiarity with developing and managing CI/CD pipelines.
Understanding of data structures and models, and hands‑on experience with analytics platforms (e.g., Power BI, Azure ML or Synapse).
Excellent communication skills.

Preferred/Nice to Have

Prior experience in property & casualty insurance.
Bachelor’s degree in computer science or a related engineering field.
Certifications in cloud data platforms (e.g., AWS Certified Data Analytics, Azure Data Engineer Associate).
Familiarity with generative AI and large‑language‑model technologies.