Description
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.
Requirements
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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Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
- Dice Id: rhalfint
- Position Id: 03720-0013512453
- Posted 1 day ago
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