Senior Snowflake Data Engineer

The project is for one of the world's famous science and technology companies in pharmaceutical industry, supporting initiatives in AWS, AI and data engineering, with plans to launch over 20 additional initiatives in the future. Modernizing the data infrastructure through the transition to Snowflake as a priority, as it will enhance capabilities for implementing advanced AI solutions and unlock numerous opportunities for innovation and growth.

We are seeking a Senior Snowflake Developer who will be responsible for designing, developing, and maintaining scalable data solutions that effectively meet the needs of our organisation.

The role will serve as a primary point of accountability for the technical implementation of the data flows, repositories and data-centric solutions in your area, translating requirements into efficient implementations.

• Design and work with Snowflake databases, schemas, views, and RAW, STG, and MART data layers.
• Manage access using RBAC, role hierarchies, row-level security, and column-level access policies.
• Work with dynamic tables, external stages, Snowpipe, and batch data loading.
• Build and support reliable, production-grade Snowflake data pipelines.
• Write optimised SQL queries for data extraction, transformation, and loading.
• Utilise Python for advanced data processing, automation tasks, and system integration.
• Be an advisor with your In-depth knowledge of Snowflake architecture, features, and best practices.
• Develop and maintain complex data pipelines and ETL processes in Snowflake.
• Collaborate with data architects, analysts, and stakeholders to design optimal and scalable data solutions.
• Automate DBT Jobs & build CI/CD pipelines using Azure DevOps for seamless deployment of data solutions.
• Ensure data quality, integrity, and compliance throughout the data lifecycle.
• Troubleshoot, optimize, and enhance existing data processes and queries for performance improvements.
• Document data models, processes, and workflows clearly for future reference and knowledge sharing.
• Build Data tests, Unit tests and mock data frameworks
• Good to have AWS and Streamlit knowledge