Sr. Data Engineer

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R78845

By joining Sedgwick, you'll be part of something truly meaningful. It’s what our 33,000 colleagues do every day for people around the world who are facing the unexpected. We invite you to grow your career with us, experience our caring culture, and enjoy work-life balance. Here, there’s no limit to what you can achieve.

Newsweek Recognizes Sedgwick as America’s Greatest Workplaces National Top Companies

Certified as a Great Place to Work®

Fortune Best Workplaces in Financial Services & Insurance

Sr. Data Engineer

• 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.

• Performs other duties as assigned.

• Supports the organization’s quality program(s).

• Travels as required.

• Provides direct management and career mentorship to one data engineer, with potential for the team to grow.

Bachelor’s degree in computer science, information systems, data engineering, or a related field from an accredited college or university preferred.

Equivalent combination of education, professional certifications, and relevant work experience will be considered.

• 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.

• Advanced knowledge of Snowflake architecture, performance tuning, data modeling, storage structures, and secure data sharing.

• Strong knowledge of scalable batch, real-time streaming, and event-driven data pipeline architecture.

• Experience with semantic layers, including dbt Semantic Layer and Snowflake Cortex or semantic definitions.

• Strong Python skills, particularly in cloud environments and Azure Functions used for data workloads.

• Strong SQL capabilities.

• Experience with dbt highly…