Snowflake Data Engineer

The Freedom Pay Commerce Platform is the technology of choice for many of the largest companies across the globe in retail, hospitality, lodging, gaming, sports and entertainment, food service, education, healthcare and financial services. Freedom Pay’s technology has been purposely built to deliver rock solid performance in the highly complex environment of global commerce. The company maintains a world-class security environment and was first to earn the coveted validation by the PCI Security Standards Council against Point-to-Point Encryption with EMV standard in North America.

Freedom Pay’s robust solutions across payments, security, identity and data analytics are available in-store, online and on-mobile and are supported by rapid API adoption. The award winning Freedom Pay Commerce Platform operates on a single, unified technology stack across multiple continents allowing enterprises to deliver a consistent, repeatable experience on a global scale. Freedom Pay is a fast paced, high growth company with a great culture with competitive benefits and compensation with a business casual atmosphere.

We are seeking a Snowflake Data & AI Engineer to design, build, and operationalize production‑grade data and artificial intelligence solutions on Snowflake. This person should bring hands‑on experience developing data pipelines, data models, integrations, and AI‑powered applications in a production environment and be comfortable working across Snowflake SQL, Cortex AI, semantic views, agent development, and modern data engineering patterns.

This role is designed around engineering and delivery responsibilities, including building trusted data products, implementing scalable ingestion and transformation pipelines, developing and maintaining AI agents, and enabling secure data sharing. The engineer will partner with the Snowflake Account Administrator, security, and infrastructure teams on account‑level access, governance, identity, cost controls, and platform configuration rather than owning those administrative functions.

This is a mid level engineering role focused on production delivery, solution ownership, and technical leadership for Snowflake‑based data and AI capabilities. The engineer is expected to independently drive implementation decisions, establish durable engineering patterns, and coordinate with platform, security, infrastructure, and business stakeholders while keeping account administration responsibilities clearly separated.

• Design, build, test, deploy, and maintain scalable data pipelines, transformations, and data models on Snowflake.
• Develop and product ionize AI and machine learning solutions using Snowflake Cortex AI, including AI agents, retrieval and search experiences, and external-facing applications.
• Create, validate, version, and maintain semantic views and related business logic to support accurate, governed AI and analytics experiences.
• Build and support ingestion patterns using Snowflake Openflow, Kafka, Snowpipe, APIs, and third‑party connectors, including integrations with enterprise applications such as Net Suite.
• Develop reusable engineering components and automation using advanced SQL, SnowSQL or Snowflake CLI, Python, and, where appropriate, JavaScript.
• Implement data quality checks, automated testing, observability, error handling, and deployment controls to ensure reliable production data and AI workloads.
• Optimize data models, queries, pipelines, and AI workloads for performance, maintainability, scalability, and efficient consumption.
• Design and implement secure Snowflake data sharing and data‑product patterns for internal teams, partners, and customers.
• Establish software engineering practices for Snowflake development, including source control, CI/CD, environment promotion, documentation, and release management.
• Troubleshoot pipeline, application, semantic‑layer, and data‑quality issues and drive them through resolution.
• Partner with the Snowflake Account Administrator and security teams on required roles, privileges, SSO/SCIM integration, governance policies, and production readiness without assuming ownership of account administration.
• Collaborat…