Senior Cloud Data Engineer​/Modern Data Stack Focus

Job Summary

The Enterprise BI & Analytics Team serves as the enterprise data and analytics center of excellence at Webstaurant Store. We transform billions of data points across marketing, supply chain, operations, and customer experience into trusted data foundations and actionable insights. Leveraging a modern cloud data platform, a scalable ELT architecture, and automated Data Ops workflows, the team empowers smarter decisions, rapid growth, and new opportunities across the business.

As a Senior Cloud Data Engineer, you will architect and own the next generation of our modern data ingestion and integration ecosystem. You will lead the development of a unified ingestion framework into Snowflake—building scalable, automated, and high-throughput data pipelines that power analytics and data products enterprise-wide. You will play a key role in our data warehouse modernization initiative, guide our transition from SQL Server to Snowflake, mentor engineers, and help define the future state of our cloud data architecture.

• Lead the design and implementation of a standardized ELT-based ingestion framework into Snowflake.
• Design scalable ingestion pipelines for structured and semi-structured data from APIs, databases, cloud storage, flat files, and collaboration platforms.
• Build and maintain Fabric Pipelines to support cloud-native orchestration and pipeline automation.
• Develop reusable Python libraries and ingestion accelerators to standardize engineering practices.
• Implement robust monitoring, logging, and data reliability engineering practices to ensure SLA adherence.
• Refactor and optimize legacy ingestion processes to align with modern data stack best practices.
• Drive and support the migration from SQL Server to Snowflake.

• Act as the lead architect for enterprise ingestion strategy, mentoring engineers and guiding technical design decisions.
• Champion best practices in CI/CD, version control, automated testing, and infrastructure-as-code principles within the data engineering function.
• Perform code reviews and enforce architectural standards.
• Partner with BI leadership to plan capacity, prioritize initiatives, and execute delivery roadmaps.
• Foster a culture of engineering ownership, accountability, and innovation.

• Collaborate with business and analytics stakeholders to translate requirements into scalable ingestion designs.
• Evaluate emerging tools and technologies within the modern data stack ecosystem.
• Contribute to long-term cloud data strategy and architectural evolution.
• Ensure enterprise-grade governance, security, compliance, and data quality controls.

• Work is performed while sitting/standing and interfacing with a personal computer.
• Requires the ability to communicate effectively using speech, vision, and hearing.
• Requires the regular use of hands for simple grasping and fine manipulations.
• Requires occasional bending, squatting, crawling, climbing, and reaching.
• Requires the ability to occasionally lift, carry, push, or pull medium weights, up to 50lbs.

• Access to a reliable and secure high-speed internet connection (at least 75mbps download/10mbps upload).
• Access to a home router and modem.
• A dedicated home office space that is noise- and distraction-free.
• A valid, physical address (PO Boxes are not supported).
• The desire and ability to work and communicate with other team members via chat, webcam, etc.
• Legal residents of one of the following states: AK, AL, AR, AZ, CT, DE, FL, GA, IA, , IN, KS, KY, LA, MD, ME, MI, MN, MO, MS, MT, NC, ND, NE, NH, NM, NV, OH, OK, PA, SC, SD, TN, TX, UT, VA, VT, WI, WV, or WY.
• H-1B Visa Sponsorship Not Available, W2 only.

• Bachelor's degree in Computer Science, Engineering, Information Systems, or related discipline; or equivalent experience.
• 7–10 years of experience in data engineering or cloud data development roles.
• 5 years of hands‑on Snowflake experience, including ingestion architecture, performance optimization, and workload management.
• 4–6 years building pipelines using Microsoft Fabric Pipelines or comparable orchestration…