Senior Data Engineer: Snowflake & Cloud Data Pipelines Lead

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

Job summary

Sedgwick is seeking a Senior Data Engineer to design, build, and maintain scalable data pipelines across batch, streaming, and event-driven data flows. You will be a core Snowflake developer, focusing on performance tuning, data modeling, and secure data sharing, while guiding decentralized teams in data engineering best practices.

Ideal candidates bring 5+ years of production-grade data engineering experience, strong Python and SQL skills, and expertise with Snowflake, dbt, and Azure/AWS data

Qualifications

• Five (5)+ years of dedicated data engineering experience building production-grade data pipelines.
• Advanced hands-on experience with Snowflake architecture, performance tuning, and data sharing.
• Experience moving data across hybrid environments (on-prem to cloud) 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; optimize performance and data sharing.
• Architects transformation pipelines delivering high-quality inputs to Snowflake and dbt AI features.
• Builds semantic layers and metadata models for Self-Service 2.0 NL interfaces.
• Establishes reference architectures, templates, and CI/CD practices for decentralized teams.

Skills

Snowflake architecture

Python

SQL

Data modeling

CI/CD

Data pipelines

Cross-functional leadership

Analytical thinking

Communication

Education

Bachelor's degree in Computer Science / Information Systems / Data Engineering or related field

Tools

Snowflake

dbt

Azure Data Factory

Azure Functions

Stream Analytics

AWS data ecosystems

Job description

Sedgwick is seeking a Senior Data Engineer to design, build, and maintain scalable data pipelines across batch, streaming, and event-driven data flows. You will be a core Snowflake developer, focusing on performance tuning, data modeling, and secure data sharing, while guiding decentralized teams in data engineering best practices.

Ideal candidates bring 5+ years of production-grade data engineering experience, strong Python and SQL skills, and expertise with Snowflake, dbt, and Azure/AWS data