Senior Data Engineer

Alliance Laundry System • Ripon, WI

74d

About The Position

The Enterprise Analytics Center of Excellence (CoE) is building the next-generation analytics stack centered on Snowflake (AWS) and Sigma. We are looking for a Sr Data Engineer who will play a critical role in shaping and operating this modern architecture. This role is not just about maintaining pipelines. It's about helping lead the way in adopting cutting-edge analytics practices, scaling governed data models, and exploring new trends in the industry.

Requirements

• Bachelor's degree in computer science or related field, required.
• Snowflake expertise: SQL, OpenFlow, Tasks/Streams, performance tuning, semantic views.
• Strong hands-on with AWS (S3, IAM, Glue, Lambda a plus).
• Proven ability to build and optimize large-scale pipelines.
• AD/LDAP integration, RBAC, cataloging.
• SQL required; Python required.
• Curiosity and enthusiasm for cutting-edge analytics tools and approaches.

Nice To Haves

• Experience migrating Power BI models/reports into Snowflake + Sigma.
• Familiarity with Sigma features: Ask Sigma, Write-Back, Embedded Analytics.
• Exposure to Dataiku (to support migration away from it).
• Interest in AI/ML-powered analytics and NLP-based BI interfaces.

Responsibilities

• Design, build, and maintain scalable data pipelines in Snowflake OpenFlow and other Snowflake-native services.
• Migrate existing Dataiku pipelines to Snowflake, reducing complexity and cost.
• Continuously improve workflows for performance, reliability, and efficiency.
• Create and maintain Snowflake semantic views that serve as the governed data layer for analytics.
• Apply dimensional modeling best practices to ensure consistency and reusability across business domains.
• Enable role-based semantic views for Finance, Operations, and other enterprise functions.
• Implement and maintain RBAC frameworks using Active Directory roles/groups.
• Support metadata management and cataloging surfaced directly in Sigma.
• Ensure pipelines and models comply with enterprise data governance standards.
• Deliver clean, governed data sets for Sigma dashboards, Ask Sigma (NLP), Write-Back, and embedded analytics.
• Monitor and tune query performance to optimize cost and speed.
• Provide technical depth to ensure analytics can scale securely and efficiently across the enterprise.
• Stay on top of the latest trends in data engineering and analytics (semantic layers, LLM-powered BI, write-back, real-time pipelines, etc.).
• Bring new ideas and emerging technologies to ALS for evaluation and potential adoption.
• Automate testing, monitoring, and deployment processes to keep the stack modern and efficient.

What This Job Offers

• Job Type: Full-time
• Industry: Machinery Manufacturing
• Education Level: Bachelor's degree