Senior Cloud Data Engineer — Snowflake ELT & Ingestion

WebstaurantStore; Lititz (Lancaster County); Hybrid; USD 140,000 - 200,000; Full time

Benefits offered by this job

Medical

Dental

401(k) matching

Paid PTO

Bonus Opportunities

Job summary

WebstaurantStore is hiring a Senior Cloud Data Engineer to architect and own the modernization of our data ingestion and integration ecosystem. You will lead Snowflake onboarding, migrate from SQL Server, mentor engineers, and shape our cloud data architecture across analytics, marketing, supply chain, and operations.

Join a fast-growing data platform team building scalable pipelines, reusable libraries, and robust observability to enable enterprise-wide data products and trusted insights.

Qualifications

• 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 frameworks.
• 4–6 years of Python development for data automation and pipeline engineering.
• 5+ years of advanced SQL experience, including deep expertise in SQL Server and CDC methodologies.
• 5+ years operating in Agile/Scrum delivery environments.
• 3+ years in a technical leadership capacity within data engineering initiatives.
• Experience with event‑based ingestion, streaming pipelines, or data contract–driven architectures.
• Experience with Qlik Replicate and dbt Cloud.
• Microsoft Azure experience.
• Relevant cloud or data platform certifications preferred.

Responsibilities

• Lead 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.

Skills

Python

SQL

Agile/Scrum

Data engineering

Leadership

Education

Bachelor’s degree in CS/Engineering or related field

Tools

Snowflake

Microsoft Fabric Pipelines

dbt Cloud

Qlik Replicate

Azure

Job description

WebstaurantStore is hiring a Senior Cloud Data Engineer to architect and own the modernization of our data ingestion and integration ecosystem. You will lead Snowflake onboarding, migrate from SQL Server, mentor engineers, and shape our cloud data architecture across analytics, marketing, supply chain, and operations.

Join a fast-growing data platform team building scalable pipelines, reusable libraries, and robust observability to enable enterprise-wide data products and trusted insights.