Systems Engineer - Mid

Role

Systems Engineer - Mid

Tasks/Responsibilities

• Manage and optimize Snowflake and Databricks environments, including performance tuning, cost controls, workload isolation, and scaling; provide secondary support for Azure SQL and Azure Data Factory.
• Build and maintain data pipelines using Databricks, Snowflake Streams/Tasks, and Azure Data Factory.
• Enforce security and governance controls including RBAC, encryption, auditing, masking, lineage, and Entra ID (Azure AD) integration.
• Tune queries and workloads using native tools such as Snowflake Query Profile, Databricks SQL Analytics, and Azure Monitor.
• Implement and maintain disaster recovery, replication, backup, and archival strategies across platforms.
• Collaborate with data engineers, data scientists, BI teams, and architects to support scalable data models, integrations, and reporting.
• Provide production support, incident response, and root-cause analysis for data platform issues.
• Evaluate and adopt new platform features (e.g., Snowflake Native Apps, Databricks Unity Catalog) to improve governance and automation.

Required Skills/Experience

• Hands-on Snowflake administration: warehouse management, query tuning, clustering, caching, cost governance, Time Travel, and replication.
• Hands-on Databricks administration: workspaces, clusters, SQL Warehouses, jobs, policies, and workload isolation.
• Experience with Databricks Unity Catalog, data governance, lineage, and access controls.
• Proficiency in SQL and scripting with Python and/or PowerShell.
• Experience with Azure data services (Data Factory, Databricks, Azure SQL), including connectivity, authentication, and monitoring.
• Strong understanding of platform security: RBAC, encryption, auditing, masking, and Entra ID integration.
• Experience with backup, recovery, and DR strategies including Snowflake replication and Time Travel.
• Proven production support skills with ability to resolve complex, cross-platform incidents.
• Familiarity with CI/CD and DevOps practices for data platform deployments.
• Solid documentation skills — SOPs, runbooks, architecture diagrams, and DR plans.
• Clear communicator who works well with both technical and non-technical stakeholders.
• Awareness of AI services relevant to platform administration.

Education

• BS in Computer Science, Engineering, Information Systems, or equivalent practical experience (typically 5–7+ years) in data platforms, database administration, or software engineering.