Senior Data Engineer: Snowflake, dbt & Cloud Pipelines

Sedgwick; Arkansas; On-site; USD 120,000 - 180,000; Full time

Job summary

Sedgwick in the United States is seeking a Sr. Data Engineer to design, build and maintain scalable data pipelines across on-prem and cloud, focusing on Snowflake, dbt AI features, and semantic models.

You will mentor a data engineer, advance CI/CD practices, and evaluate AWS/Azure data tools for optimized data flow, with a strong emphasis on governance and cross-functional collaboration.

Qualifications

• Five (5)+ years of dedicated data engineering experience, with a proven record of building production-grade data pipelines.
• Advanced hands-on experience with Snowflake architecture, performance tuning, and data sharing.
• Experience moving data across hybrid environments, including on-premises to cloud, using batch, streaming, and event-driven patterns.
• Experience building or maintaining semantic layers and structuring data for downstream AI, large language model, or natural-language search capabilities.

Responsibilities

• Designs, builds, and maintains scalable data pipelines supporting batch, real-time streaming, and event-driven data movement from on-premises and cloud sources.
• Serves as a core developer for the Snowflake data platform and supports platform performance, data modeling, and storage structures.
• 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.

Skills

Snowflake

dbt

Python

SQL

Azure Functions

Azure Data Factory

Data pipelines

CI/CD

Leadership

Data modeling

Education

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

Tools

Azure Data Factory

Stream Analytics

dbt Semantic Layer

Job description

Sedgwick in the United States is seeking a Sr. Data Engineer to design, build and maintain scalable data pipelines across on-prem and cloud, focusing on Snowflake, dbt AI features, and semantic models.

You will mentor a data engineer, advance CI/CD practices, and evaluate AWS/Azure data tools for optimized data flow, with a strong emphasis on governance and cross-functional collaboration.