Senior Data Engineer: Snowflake, dbt & Cloud Pipelines

Sedgwick; Tennessee; On-site; USD 111,000 - 200,000; Full time

Benefits offered by this job

Medical benefits

Dental benefits

Vision benefits

401k with matching

PTO

Job summary

Sedgwick is seeking a Sr. Data Engineer to design and maintain scalable data pipelines, focusing on Snowflake, dbt, and cloud-based data tools. You will lead data platform development, mentor a data engineer, and collaborate with cross-functional teams to enable AI-ready data products.

The role emphasizes hands-on Snowflake architecture, batch and streaming data movement, and the delivery of reliable data inputs for analytics and AI initiatives in a modern hybrid-cloud environment.

Qualifications

• Bachelor's degree in computer science, information systems, data engineering, or related field preferred.
• Five (5)+ years of dedicated data engineering experience building production-grade pipelines.
• Advanced hands-on with Snowflake architecture, performance tuning, and data sharing.
• Experience moving data across hybrid on-premises to cloud environments using batch, streaming, and event-driven patterns.

Responsibilities

• Designs, builds, and maintains scalable data pipelines for batch, real-time streaming, and event-driven movement.
• Core developer for Snowflake data platform; supports performance, modeling, and storage structures.
• Architects transformation pipelines delivering high-quality inputs to Snowflake and dbt AI features.
• Maintains semantic layers and metadata to support Self-Service 2.0 language interfaces.

Skills

Snowflake

Python

SQL

Data pipelines

Leadership

Cloud environments

Education

Bachelor's degree (CS/IS/related)

Tools

Snowflake

dbt

Azure Data Factory

Azure Functions

Stream Analytics

AWS data tools

Job description

Sedgwick is seeking a Sr. Data Engineer to design and maintain scalable data pipelines, focusing on Snowflake, dbt, and cloud-based data tools. You will lead data platform development, mentor a data engineer, and collaborate with cross-functional teams to enable AI-ready data products.

The role emphasizes hands-on Snowflake architecture, batch and streaming data movement, and the delivery of reliable data inputs for analytics and AI initiatives in a modern hybrid-cloud environment.