Senior Data Engineer: Snowflake, dbt & Data Pipelines

Sedgwick; East Honolulu (HI); On-site; USD 111,000 - 200,000; Full time

Job summary

Sedgwick in Honolulu, Hawaii, is seeking a Senior Data Engineer to design, build, and maintain scalable data pipelines supporting batch, real-time streaming, and event-driven movement from on‑premises to the cloud, with a strong emphasis on Snowflake, data modeling, and storage structures.

You will architect semantic layers, templates, and CI/CD practices, mentor one data engineer, and collaborate with cross‑functional teams to enable safe data product delivery and AI/LLM readiness.

Qualifications

• Five (5)+ years of dedicated data engineering experience required.
• Advanced hands-on experience with Snowflake, performance tuning, and data sharing.
• Experience moving data across hybrid on-premises to cloud environments.
• Experience building semantic layers to support AI, large language model, or natural-language search capabilities preferred.

Responsibilities

• Designs, builds, and maintains scalable data pipelines for batch, real-time streaming, and event-driven data movement from on-premises and cloud sources.
• Architects and builds transformation pipelines that deliver high-quality data inputs to Snowflake and dbt AI features.
• Designs and maintains semantic layers and metadata models required to support Self-Service 2.0 natural-language user interfaces.
• Establishes reference architectures, reusable templates, and CI/CD best practices that enable decentralized line-of-business teams to build data products safely and consistently.

Skills

Snowflake architecture

Data pipelines

Python

SQL

dbt

Azure Functions

Azure Data Factory

Stream Analytics

AWS data ecosystems

Data modeling

Data sharing

Education

Bachelor’s degree in computer science, information systems, data engineering, or a related field

Job description

Sedgwick in Honolulu, Hawaii, is seeking a Senior Data Engineer to design, build, and maintain scalable data pipelines supporting batch, real-time streaming, and event-driven movement from on‑premises to the cloud, with a strong emphasis on Snowflake, data modeling, and storage structures.

You will architect semantic layers, templates, and CI/CD practices, mentor one data engineer, and collaborate with cross‑functional teams to enable safe data product delivery and AI/LLM readiness.