Senior Snowflake Engineer – AI & Data Platform

Job Title: Senior Snowflake Engineer – AI & Data Platform

Location: Remote

Duration: Long Term 

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.