You'll be at the forefront of designing and implementing robust data platform solutions, specifically tailored to fuel our client's ambitions. Leveraging the latest data platforms and tooling, you will build the foundational data layers for advanced analytics, AI and machine learning. You'll get to sink your teeth into exciting projects like:

• Engineering data pipelines: Building efficient and scalable data pipelines that feed clean, curated data into machine learning models on AWS, Snowflake, GCP and Databricks.
• Optimizing data for AI consumption: Designing data models and transformations within Snowflake to ensure data is in the perfect format for training, validating, and deploying AI models.
• Integrating diverse data sources for AI insights: Connecting disparate data systems into platforms like Snowflake to create comprehensive datasets for advanced AI analytics and predictive modeling.
• Leveraging Snowflake's AI capabilities: Exploring and implementing Snowflake's native AI and machine learning features (like Snowpark ML) to enhance data processing and model deployment.
• Supporting the data-driven heart of AI transformations: Playing a critical role in bringing AI strategies to life by ensuring the underlying data infrastructure is robust, secure, and performant.

What We Are Looking for

• 8 to 12 years hands-on experience with Snowflake data warehouse, including its core architecture and advanced features.
• Strong proficiency in SQL and Python for data processing, scripting, and integrating with the Snowflake API. Experience with other languages like Scala or Java is a plus.
• Significant experience with at least one major cloud provider (AWS, Azure, or GCP), specifically with their data storage services (e.g., S3, ADLS, GCS)
  • A deep understanding of various data modeling techniques, such as dimensional modeling (star and snowflake schemas) and data vault, is expected.