Senior Data Engineer - Snowflake, Spark & RealTime Pipelines

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

Job summary

Sedgwick is hiring a Sr. Data Engineer to design and maintain scalable data pipelines, primarily on Snowflake, dbt, and cloud-based tools. You will mentor a junior engineer and collaborate with cross-functional teams to deliver robust data products.

Responsibilities include architecture, data modeling, and implementing CI/CD patterns while enabling AI-ready data pipelines for analytics and search capabilities.

Qualifications

• Bachelor’s degree in computer science, information systems, data engineering, or related field preferred.
• Equivalent combination of edu, certs, and experience will be considered.

Responsibilities

• Designs, builds, and maintains scalable data pipelines for batch, real-time streaming, and event-driven data movement.
• Core developer for Snowflake data platform focusing on performance, modeling, and storage structures.
• Architects and builds transformation pipelines delivering high-quality data inputs to Snowflake and dbt AI features.
• Maintains semantic layers and metadata models to support Self-Service 2.0 NL interfaces.
• Establishes reference architectures, reusable templates, and CI/CD best practices for decentralized teams.
• Provides direct management and mentorship to one data engineer and guides data analysts in engineering practices.
• Drives dbt adoption and evaluates AWS and Azure cloud data tools to optimize data flow.

Skills

leadership

mentoring

communication

problem solving

Education

Bachelor's degree in CS/IS/Data Engineering

Tools

Snowflake

dbt

Azure Functions

Azure Data Factory

Stream Analytics

Python

SQL

AWS data tools

CI/CD

Job description

Sedgwick is hiring a Sr. Data Engineer to design and maintain scalable data pipelines, primarily on Snowflake, dbt, and cloud-based tools. You will mentor a junior engineer and collaborate with cross-functional teams to deliver robust data products.

Responsibilities include architecture, data modeling, and implementing CI/CD patterns while enabling AI-ready data pipelines for analytics and search capabilities.