Senior Snowflake Engineer – AI & Data Platform
eCom Solutions Inc· enterprise· Information Technology And Services· Jul 9, 2026 · 4mo agoPosted 110 days ago
United States
Remote
Full-time
Senior
$70/hr
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Ghost Signal:
Open since July 9, 2026 — 110 days, and still accepting applications.
Job description
Job Title: Senior Snowflake Engineer – AI & Data Platform
Location: Remote
Duration: Long Term
Pay Rate: $70/hr on C2C
Senior Snowflake Engineer – AI & Data Platform
Role Overview
We are seeking a highly skilled Senior Snowflake Engineer to design, build, and optimize scalable cloud data platforms using Snowflake , modern data engineering practices, and AI-enabled capabilities. The ideal candidate will have deep experience in Snowflake architecture, data modeling, performance tuning, ELT pipelines, and cloud data integration, with exposure to AI/ML workloads, Snowpark, Snowflake Cortex, or GenAI-enabled data solutions.
This role will partner with data architects, analytics teams, AI/ML engineers, and business stakeholders to deliver high-quality, secure, and performant data solutions that support analytics, reporting, machine learning, and enterprise AI initiatives.
Key Responsibilities
• Design, develop, and optimize Snowflake-based data warehouse and data lakehouse solutions.
• Build scalable ELT/ETL pipelines using tools such as dbt, Informatica, Matillion, Fivetran, Airflow, or similar platforms.
• Develop complex SQL queries, stored procedures, tasks, streams, dynamic tables, and data transformation logic.
• Optimize Snowflake performance through clustering, partitioning strategy, warehouse sizing, query tuning, caching, and cost governance.
• Implement secure data access using Snowflake RBAC, data masking, row-level security, secure views, and governance best practices.
• Support AI and ML use cases by enabling curated, governed, and AI-ready data products.
• Work with Snowpark, Python, or Snowflake Cortex capabilities to support AI/ML feature engineering, model integration, and GenAI-driven analytics.
• Collaborate with data science and AI teams to prepare trusted datasets for predictive analytics, LLM applications, and enterprise AI agents.
• Design data ingestion patterns from structured, semi-structured, and unstructured sources including APIs, cloud storage, databases, and streaming platforms.
• Develop reusable data engineering frameworks, templates, automation scripts, and deployment standards.
• Support CI/CD, DevOps, and release management for Snowflake objects and data pipelines.
• Monitor data quality, pipeline health, job performance, and platform utilization.
• Troubleshoot production issues, identify root causes, and implement long-term fixes.
• Provide technical leadership, code reviews, mentoring, and guidance to junior data engineers.
• Partner with business and architecture teams to translate requirements into scalable technical solutions.
Required Skills and Experience
• 8+ years of experience in data engineering, data warehousing, or cloud data platforms.
• 4+ years of hands-on experience with Snowflake development and administration.
• Strong expertise in SQL, data modeling, ELT/ETL design, and performance tuning.
• Experience with Snowflake features such as warehouses, databases, schemas, stages, pipes, tasks, streams, secure views, time travel, cloning, and data sharing.
• Hands-on experience with one or more cloud platforms: AWS, Azure, or Google Cloud.
• Experience integrating Snowflake with cloud storage such as Amazon S3, Azure Data Lake, or Google Cloud Storage.
• Experience with Python, Snowpark, or similar data engineering programming frameworks.
• Familiarity with AI/ML data preparation, feature engineering, model consumption, or GenAI use cases.
• Experience with orchestration and transformation tools such as Airflow, dbt, Matillion, Informatica, or Fivetran.
• Strong understanding of data governance, security, data quality, and metadata management.
• Experience with CI/CD tools such as GitHub, GitLab, Jenkins, Azure DevOps, or Terraform.
• Strong problem-solving, communication, and stakeholder-management skills.
Preferred Qualifications
• SnowPro Core or SnowPro Advanced certification.
• Experience with Snowflake Cortex, Snowpark ML, vector search, semantic models, or AI-powered analytics.
• Experience supporting LLM, GenAI, or enterprise AI-agent use cases on governed enterprise data.
• Experience with real-time or near-real-time data pipelines using Kafka, Snowpipe Streaming, or similar technologies.
• Experience in healthcare, financial services, retail, life sciences, or regulated enterprise environments.
• Experience with data catalog, lineage, and governance tools such as Collibra, Alation, Informatica EDC, or Microsoft Purview.
Application prep
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