Senior Data Engineer - Snowflake & Real-Time Pipelines

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

Job summary

Sedgwick is seeking a Sr. Data Engineer to design, build, and maintain scalable data pipelines across on‑premises and cloud sources, with strong Snowflake knowledge and a focus on data quality and performance.

You will work on transforming data inputs for Snowflake and dbt AI features, develop semantic layers for Self-Service 2.0 NL interfaces, and promote CI/CD practices across the data platform while mentoring a data engineer.

Qualifications

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

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.
• Establishes reference architectures, reusable templates, and CI/CD best practices that enable decentralized line-of-business teams to build data products safely and consistently.
• Provides direct management and career mentorship to one data engineer, with potential for team growth, and guides decentralized data analysts in maturing their engineering practices.
• Drives adoption of dbt for data transformation and evaluates the integration of AWS and Azure cloud data tools, including Azure Data Factory, Azure Functions, and Stream Analytics, to optimize data flow.

Skills

Snowflake architecture

Python

SQL

Azure Functions

dbt

Data pipelines

CI/CD

Data modeling

Cloud data tools

Education

Bachelor's degree in CS

Tools

dbt

Azure Data Factory

Stream Analytics

AWS data tools

Job description

Sedgwick is seeking a Sr. Data Engineer to design, build, and maintain scalable data pipelines across on‑premises and cloud sources, with strong Snowflake knowledge and a focus on data quality and performance.

You will work on transforming data inputs for Snowflake and dbt AI features, develop semantic layers for Self-Service 2.0 NL interfaces, and promote CI/CD practices across the data platform while mentoring a data engineer.