Job Summary
Key ResponsibilitiesUser Access & Security Management• Process and fulfill user access requests within established SLAs (2-24 hour turnaround)• Manage database, schema, table, and view permissions using role-based access control (RBAC)• Create and configure user accounts, roles, and privileges following security best practices• Implement OAuth 2.0 integrations and manage authentication mechanisms• Conduct security compliance monitoring including privileged access reviews and PII data access audits• Monitor and respond to failed login attempts and security alertsPlatform Operations & Incident Management• Respond to and resolve incidents related to Snowflake platform performance and availability• Monitor warehouse utilization, query performance, and system health using Snowflake account usage views• Troubleshoot connection issues, authentication failures, and query execution problems• Manage warehouse configuration including sizing, auto-suspend, auto-resume, and multi-cluster settings• Coordinate with Matillion team on ETL job monitoring and pipeline troubleshooting• Document incident resolution procedures and contribute to knowledge base articlesQuery Optimization & Performance Tuning• Analyse slow-running queries and recommend optimization strategies (clustering, materialized views, result caching).• Monitor query profiles, execution statistics, and recommend warehouse sizing adjustments• Use Snowflake Intelligence and Cortex Analyst for natural language query analysisCost Management & Resource Governance• Monitor credit consumption and identify cost anomalies or unusual spending patterns• Configure and manage resource monitors with credit quotas and alert thresholds• Analyze warehouse idle time and recommend auto-suspend optimizations• Track storage costs including Time Travel, Fail-safe, and database growth trends• Support the team's cost optimization initiativesData Integration & Pipeline Support• Support cross-cloud data replication between AWS and Azure environments• Configure and monitor Tasks for continuous data ingestion• Manage external stages, file formats, and data loading processes• Collaborate with administrators on ETL job dependencies and database objects• Support Power BI, Tableau, and other BI tool integrations with SnowflakeRequired QualificationsTechnical Skills• 2-4 years of hands-on Snowflake administration experience in enterprise environments• Strong proficiency in SQL including complex queries, stored procedures, and performance optimization• Deep understanding of Snowflake architecture: virtual warehouses, micro-partitions, clustering, time travel• Experience with RBAC, user management, and security configurations in Snowflake• Proficiency with Snowflake account usage views and query optimization techniques• Working knowledge of data warehousing concepts, ETL processes, and dimensional modeling• Familiarity with cloud platforms (AWS, Azure) and data integration toolsSoft Skills• Strong customer service orientation with ability to communicate technical concepts to non-technical users• Excellent problem-solving skills and ability to troubleshoot under pressure• Detail-oriented with strong organizational and time management capabilities• Ability to work independently and collaboratively in a fast-paced environment• Proactive approach to identifying and resolving issues before they impact users
Key Responsibilities
2. Collaborate with cross functional teams to gather data requirements, design data pipelines, and ensure data quality and integrity.
3. Provide technical guidance and mentorship to team members on best practices for utilizing snowflake, azure data factory (adf), and data bricks.
4. Troubleshoot and resolve technical issues related to data pipelines, data transformation, and data storage in snowflake, azure data factory (adf), and data bricks.
5. Stay updated on industry trends and best practices related to snowflake, azure data factory (adf), and data bricks to recommend and implement improvements in existing data processes.
Skill Requirements
2. Handson experience with azure data factory (adf) including data pipeline development, integration, and monitoring.
3. Strong knowledge of data bricks for big data processing, data engineering, and machine learning workflows.
4. In-depth understanding of data warehousing concepts, etl processes, and data modeling techniques.
5. Excellent problem-solving skills and ability to work in a fast paced environment.
6. Strong communication and leadership skills to effectively collaborate with team members and stakeholders.