AWS Data EngineerDeveloping data pipelines in Python, Spark, or SQL to push structured enterprise tool telemetry to our data lake. Fine-grained access control for data exploration.Terraform infrastructure-as-code for managing AWS infrastructure and deep integration between enterprise tools (Databricks and Privacera).Evaluating Databricks capabilities to sync Hive, Glue, and Unity Catalogs.Evaluating Privacera capabilities or building new capabilities (AWS Lambda with Python) to sync Intuit access policies with Unity Catalog.Testing user flows for data analysis, processing, and visualization with Python Spark notebooks on distributed compute or Databricks’ serverless SQL runtime.Responsibilities:Develop and implement operational capabilities, tools, and processes that enable highly available, scalable, and reliable customer experiences.Resolve defects/bugs during QA testing, pre-production, production, and post-release patches.Work cross-functionally with various Intuit teams including: product management, analysts, data scientists, and data infrastructure.Work with external enterprise support engineers from Databricks, Starburst, and Privacera to resolve integration questions and issues.Experience with Agile Development, SCRUM, or Extreme Programming methodologies.