Senior Data Engineer: Snowflake, dbt & Real-Time Pipelines

Sedgwick; Helena (MT); Sur place; USD 111 000 - 200 000; Plein temps

Résumé du poste

Sedgwick in the United States is seeking a Sr. Data Engineer to design, build, and maintain scalable data pipelines across batch and real-time workloads, connecting on-premises and cloud sources, and optimizing Snowflake-driven workflows.

You will mentor a data engineer, collaborate with analytics teams, and advance CI/CD practices, dbt adoption, and cloud data tool integrations (Azure, AWS). Strong Python and SQL skills required; a CS or data engineering degree is preferred.

Qualifications

• Bachelor's degree in computer science, information systems, data engineering, or related field 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.
• Strong knowledge of Snowflake architecture, performance tuning, data modeling, storage structures, and secure data sharing.
• Strong Python skills, particularly in cloud environments and Azure Functions used for data workloads.
• Strong SQL capabilities.
• Experience with dbt highly preferred.
• Experience with Azure data tools, including Azure Data Factory, Azure Functions, and Stream Analytics, preferred.
• Familiarity with AWS data ecosystems preferred.
• Knowledge of reference architecture, reusable pipeline patterns, templates, and CI/CD practices.
• Collaborative coaching and leadership skills, with the ability to teach, establish governance, and strengthen engineering practices across cross-functional teams.
• Strong analytical, problem-solving, organizational, and communication skills.
• Ability to meet or exceed performance competencies.

Responsabilités

• 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.

Connaissances

Snowflake

Python

SQL

dbt

Azure Functions

Azure Data Factory

AWS data tools

Data modeling

Leadership

Data pipeline architecture

Formation

Bachelor's degree in computer science, information systems, data engineering, or related field

Outils

Snowflake

dbt

Azure Data Factory

Azure Functions

Stream Analytics

AWS data tools

Description du poste

Sedgwick in the United States is seeking a Sr. Data Engineer to design, build, and maintain scalable data pipelines across batch and real-time workloads, connecting on-premises and cloud sources, and optimizing Snowflake-driven workflows.

You will mentor a data engineer, collaborate with analytics teams, and advance CI/CD practices, dbt adoption, and cloud data tool integrations (Azure, AWS). Strong Python and SQL skills required; a CS or data engineering degree is preferred.