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Snowflake Data Engineer
FreedomPay. Design, build, test, deploy, and maintain scalable data pipelines, transformations, and data models on Snowflake.
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in designing and maintaining scalable data pipelines and AI solutions using Snowflake, with a strong focus on data quality, performance optimization, and collaboration across teams. Proficient in implementing software engineering practices and integrating with enterprise applications to deliver reliable data and AI workloads.
Highest-signal resume keywords
Snowflake Data EngineeringAI/ML Solution DevelopmentAdvanced SQL and SnowSQLPython ProgrammingData Pipeline Optimization
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
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Hard Skills
Snowflake SQLData Pipeline DevelopmentData Model DesignAI/ML TechnologiesSemantic Layer DesignCI/CD PracticesAutomated TestingError HandlingPerformance TuningData Quality Checks
Soft Skills
Cross-Functional CollaborationProblem SolvingCommunication
Tools & Technologies
Snowflake Cortex AIKafkaOpenflowSnowpipeAPIsAzure
Industry Keywords
Data EngineeringAI SolutionsAnalyticsEnterprise ApplicationsGovernance Policies
Tech Stack
Tools & technologiesAzureJavaScriptKafkaPythonSQL
About the role
Key responsibilities & impact- Design, build, test, deploy, and maintain scalable data pipelines, transformations, and data models on Snowflake.
- Develop and productionize 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 NetSuite.
- 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.
- Collaborate with data engineering, analytics, application, product, and business teams to translate high-value use cases into durable data and AI solutions.
Requirements
What you’ll need- Prior hands-on experience as a Snowflake data engineer, AI engineer, analytics engineer, or similar role delivering production solutions on Snowflake.
- Strong Snowflake SQL skills and demonstrated experience developing data pipelines, transformations, data models, and performance-tuned workloads.
- Experience building and maintaining applications or AI/ML solutions with Snowflake Cortex AI or comparable large language model and machine learning technologies.
- Experience designing semantic layers or semantic views that translate business concepts into governed, reusable definitions for analytics and AI.
- Proficiency in Python and experience applying software engineering practices such as testing, source control, CI/CD, and code review.
- Experience with streaming, event-driven, or connector-based ingestion using technologies such as Kafka, Openflow, Snowpipe, APIs, or comparable integration frameworks.
- Experience supporting production data platforms on Azure and integrating with enterprise identity and security patterns.
- Ability to diagnose and resolve complex data, pipeline, application, and performance issues.
- Ability to work cross-functionally with platform administration, security, data engineering, analytics, application, and business teams.
Benefits
Comp & perks- medical, prescription, dental and vision coverage
- Life Insurance
- Retirement Plans with company match
- commission sharing plan
- flexible hybrid working environment
- great parental and other leave programs