Level 2 Snowflake Support Engineer/Data Engineer

About the role

We are looking for an experienced Level 2 Snowflake Support Engineer / Data Engineer to join our Managed Services team supporting a mission-critical Snowflake data platform. This is a hands-on engineering role combining production support with modern data engineering. You’ll investigate and resolve complex incidents escalated from the Level 1 Support team, troubleshoot data pipelines, optimize Snowflake workloads, build and maintain ETL/ELT processes, and help ensure the reliability, performance, and scalability of the client’s cloud data platform. You’ll work closely with customers, internal engineering teams, and third-line specialists, playing a key role in maintaining business-critical services while continuously improving the platform through automation, optimization, and operational excellence.

What you'll do

• Production Support & Incident Resolution
• Act as the primary escalation point for complex incidents raised by the Level 1 Support team.
• Perform detailed root cause analysis of production issues affecting Snowflake and supporting cloud services.
• Troubleshoot failed data pipelines, ingestion processes, and scheduled workloads.
• Restart failed services, recover production processes, and restore platform availability.
• Escalate unresolved technical issues to third-line engineering with comprehensive analysis and supporting evidence.
• Maintain detailed incident documentation and contribute to post-incident reviews.
• Ensure all incidents are resolved within agreed SLAs.
• Snowflake Engineering
• Design, develop, and maintain scalable Snowflake data warehouses and data marts.
• Build and optimize SQL queries, stored procedures, views, and reusable data models.
• Configure and manage Snowflake databases, schemas, warehouses, stages, streams, tasks, pipes, and secure data sharing.
• Optimize query performance, warehouse utilization, storage efficiency, and overall operating costs.
• Implement role-based access controls (RBAC) and support data security and governance best practices.
• Support the ongoing modernization of legacy data warehouse environments.
• Data Engineering
• Develop and maintain ETL/ELT pipelines for structured and semi-structured data.
• Build event-driven ingestion pipelines using Snowpipe and AWS services.
• Develop reconciliation processes to validate data quality and integrity.
• Implement monitoring, validation, and error-handling across data pipelines.
• Work with JSON, Parquet, XML, and other semi-structured data formats.
• Support data migration, transformation, and integration projects.
• Collaborate with business stakeholders to deliver scalable data solutions.
• Cloud & DevOps
• Support cloud infrastructure across AWS and Snowflake environments.
• Develop and maintain GitHub repositories and deployment workflows.
• Participate in CI/CD processes, code reviews, testing, and production deployments.
• Support Infrastructure-as-Code and automation initiatives where appropriate.
• Continuously identify opportunities to improve platform reliability and operational efficiency.
• Customer & Team Collaboration
• Work directly with customer stakeholders to investigate and resolve production issues.
• Translate technical findings into clear business updates.
• Collaborate closely with Data Engineers, Platform Engineers, and Support teams.
• Maintain and improve the internal knowledge base and operational documentation.
• Participate in technical discussions and contribute to continuous service improvement

Requirements

• 4+ years of commercial experience working with Snowflake.
• Strong understanding of Snowflake architecture and administration.
• Experience with Snowpipe, Streams, Tasks, Time Travel, Zero-Copy Cloning, and Secure Data Sharing.
• Experience configuring databases, schemas, warehouses, and security roles.
• SQL & Data Engineering
• Advanced SQL development skills.
• Experience building complex stored procedures, views, and reusable data models.
• Strong understanding of dimensional modelling (Star & Snowflake Schema).
• Experience developing and maintaining ETL/ELT pipelines.
• Experience performing data reconciliation and data quality validation.
• Experience working with structured and semi-structured datasets.
• Cloud Technologies
• Commercial AWS experience, particularly S3 and SNS.
• Experience building event-driven data ingestion pipelines.
• Familiarity with cloud-native architectures and distributed data platforms.
• Data Engineering Tools
• Experience using dbt Core.
• Experience with Git and GitHub workflows.
• Familiarity with CI/CD pipelines.
• Experience with Agile software development practices.
• Programming
• Strong SQL expertise.
• Python scripting experience.
• Experience working with JSON, Parquet, XML, or similar data formats.

About Cloud Employee

Cloud Employee, is a UK-owned business established 8 years ago. We connect high-performing software engineer talent worldwide with some of the world’s leading and most innovative tech companies. Developers join to work as part of international engineering teams and grow their CV and skill set. We pride ourselves on being a supportive and cutting-edge workplace that continuously invests in staff development, engagement, and well-being. We provide security, and career paths, along with individual training programs and mentoring.

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