Intermediate AI/AWS Support Engineer

About the role

This role provides hands-on L1/L2 support for Databricks and AWS products within NextEra Energy's GSU ecosystem, including the GSU data product, Allocation Hub and Gateway. You will own day-to-day operational support, help keep critical applications and data services healthy, and use AI-assisted practices to improve troubleshooting and reusable support knowledge.

Key responsibilities

• Monitor Databricks jobs, workflows, data pipelines, Oracle API ingestion and AWS services, responding to failures, alerts, performance issues and data quality problems.
• Resolve incidents and service requests within SLAs, performing approved remediation such as job reruns, cluster restarts, configuration updates and resolution of known data issues.
• Collaborate with internal and external stakeholders and L3 product teams on end-to-end integrations, escalating complex or code-level issues with clear evidence and validating fixes.
• Troubleshoot front-end, API, backend, database, connectivity and integration issues using logs, traces, Spark UI, browser developer tools and monitoring tools.
• Manage Databricks access and permissions across workspaces, Unity Catalog, groups and service principals.
• Use AI-powered tools such as GitHub Copilot and Cursor to speed up troubleshooting, scripting, log analysis and documentation.
• Build automation scripts, runbooks, knowledge articles, known-error documentation and repeatable processes.
• Monitor platform health, performance, capacity, cost trends and observability, and contribute to root cause analysis, service reviews and backlog grooming.

Required profile

• 3-5 years of experience in cloud operations, application or data platform support, SRE or DevOps, with Databricks and AWS as the main platforms.
• Hands-on experience with Databricks jobs and workflows, clusters, SQL warehouses, Unity Catalog, Spark logs and Spark UI, and familiarity with the bronze, silver and gold medallion pattern.
• Experience with ITIL-aligned incident and request management, including priority matrices, SLAs, escalation paths and root cause analysis.
• Clear written English and a service-minded approach, especially for tickets, runbooks, end-user communication and white-glove support for business users.

Required skills

• Strong SQL, Python for debugging and scripting, and AWS services including Lambda, DynamoDB, Cognito, CloudWatch, IAM and S3.
• Integration and API troubleshooting, including logs, traces and browser developer tools.
• Working knowledge of GenAI and LLM applications, including prompts, RAG, tool or function calling, agents, production failure patterns and AI-assisted coding or operations tools.
• Beneficial: Databricks Apps, Lakebase, Delta Live Tables or Lakeflow, Databricks Asset Bundles, GitHub Actions, Terraform, ServiceNow, MCP-based integrations, Semantic Kernel, LangChain, LLM observability, Databricks AI features, SRE practices or regulated industries.