We are looking for a Snowflake Data Engineer to build modern data solutions that support analytics, AI, and enterprise decision-making. This role will focus on creating reliable pipelines, scalable data models, and secure data products within a Snowflake environment. The position is based in Radnor, Pennsylvania, and offers the opportunity to work closely with engineering, security, product, and business teams on high-impact initiatives.

Responsibilities:

• Architect and maintain scalable data pipelines, transformation workflows, and structured data models within Snowflake to support reporting, analytics, and AI use cases.
• Develop and deploy AI and machine learning capabilities using Snowflake-native tools, including intelligent agents, search-driven experiences, and customer-facing applications where applicable.
• Define and manage semantic views and business logic layers that provide governed, consistent definitions for analytics and AI consumption.
• Implement and support data ingestion frameworks using technologies such as Kafka, Snowpipe, APIs, Openflow, and third-party connectors, including integrations with enterprise platforms like NetSuite.
• Create reusable engineering utilities and automation with SQL, SnowSQL or related Snowflake tooling, Python, and JavaScript when appropriate.
• Establish strong production standards through automated testing, data quality validation, observability, exception handling, and controlled deployment processes.
• Tune queries, pipelines, AI workloads, and data structures to improve performance, scalability, maintainability, and downstream usability.
• Design secure data-sharing solutions and data-product delivery patterns for internal stakeholders, external partners, and customers.
• Collaborate with platform administrators and security teams to align access controls, governance requirements, identity integration, and production readiness for Snowflake solutions.
• Investigate and resolve issues affecting pipelines, semantic models, applications, and data quality while partnering across technical and business teams to deliver durable solutions.
• Proven experience in a Snowflake-focused engineering role, such as data engineering, analytics engineering, or AI engineering, delivering production-ready solutions.
• Strong hands-on expertise in Snowflake SQL and experience building optimized pipelines, transformations, and data models.
• Proficiency in Python and familiarity with software engineering disciplines including version control, testing, CI/CD, and peer code review.
• Experience developing AI, machine learning, or generative AI solutions using Snowflake Cortex AI or comparable technologies.
• Knowledge of semantic modeling approaches that translate business logic into reusable, governed structures for analytics and AI.
• Background working with event-driven or connector-based ingestion tools such as Kafka, Snowpipe, APIs, Openflow, or similar frameworks.
• Experience supporting cloud-based data platforms in Azure and working within enterprise identity, security, and governance standards.
• Ability to troubleshoot complex issues across data pipelines, application behavior, performance, and data quality in cross-functional environments.

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