Snowflake Data Engineer (SC Cleared) - Outside IR35 - Leeds, UK (Remote)

Key accountabilities

• Design, develop, and maintain data pipelines to ensure seamless and efficient data migration from on premise SQL Server to Snowflake on AWS, enabling secure, scalable, and reliable data storage that supports advanced analytics and reporting needs.
• Implement and manage data integration processes to unify data from multiple sources within Snowflake, ensuring high data quality, consistency, and accessibility, which drives accurate, timely insights for business users across the organisation.
• Optimise Snowflake performance by enhancing query speeds, data load times, and storage efficiency, ensuring that the data platform remains fast, responsive, and capable of handling high data volumes, which supports the organisation's operational and analytical requirements.
• Enforce data security and compliance measures by applying best practices in data encryption, access controls, and adherence to relevant regulatory standards, ensuring sensitive information remains protected and compliant throughout the migration and within Snowflake.
• Collaborate with data scientists, analysts, and key stakeholders to gather and understand data requirements, aligning Snowflake infrastructure and solutions with business needs and fostering cross-team communication to deliver reliable and actionable data.
• Evaluate and recommend complementary tools and technologies that enhance Snowflake's capabilities, keeping the data platform adaptable and current with evolving cloud technologies to ensure the organisation maximises the value of its cloud infrastructure.
• Lead migration efforts from on-premise to cloud-based infrastructure, coordinating with the Global Data Engineering Lead to establish timelines and address migration challenges, ensuring a smooth transition with minimal business disruption.
• Document and maintain data infrastructure processes and standards within the Snowflake platform to ensure knowledge sharing, consistency, and ease of maintenance, supporting long-term operational stability and team efficiency.
Top 5 Essential Criteria A proactive and methodical approach to identifying issues, troubleshooting problems, and designing long-term solutions for data architecture and processes. 1. Data Pipeline Development: Design, develop, and maintain data pipelines to ensure seamless and efficient data migration from on-premise SQL Server to Snowflake on AWS, enabling secure and reliable data storage that supports analytics and reporting. 2. Data Integration Management: Implement and manage processes to unify data from multiple sources within Snowflake, ensuring high data quality, consistency, and accessibility for accurate, timely insights. 3. Performance Optimisation: Continuously optimise Snowflake performance by enhancing query speeds, data load times, and storage efficiency to meet the organisation's operational and analytical needs. 4. Data Security and Compliance: Enforce security and compliance measures by applying best practices in data encryption and access controls to protect sensitive information and ensure adherence to regulatory standards. 5. Collaboration with Stakeholders: Collaborate with data scientists, analysts, and key stakeholders to gather and understand data requirements, aligning the Snowflake infrastructure with business needs and fostering effective communication across teams.