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About the Role: Grade Level (for internal use): 12 Key Responsibilities Data Pipeline Transition and Platform Delivery • Partner with the core Databricks team to plan and execute the transition of existing data pipelines to the target data platform. • Drive the implementation of repeatable engineering patterns for ingestion, transformation, testing, deployment, and monitoring across onboarded datasets. • Ensure pipelines are designed and managed in a way that supports long-term platform consistency, reliability, observability, and ease of support. • Guide the design and operation of cloud-native data pipelines using AWS services such as: • Amazon S3 for durable data lake storage • AWS Glue for integration, cataloging, and processing • AWS Lambda for event-driven processing • Amazon Kinesis for streaming use cases • AWS Lake Formation for governed data lake controls • Promote the use of AWS IAM, encryption, environment-level controls, and platform guardrails to enforce secure access to platform resources and data products. • Support practical application of lakehouse technologies and concepts such as Delta Lake, Apache Iceberg, Databricks Unity Catalog, metadata-driven pipelines, and governed data access patterns. Data Onboarding and Asset-Agnostic Enablement • Define and operationalize onboarding patterns that support a broad range of data assets, domains, and source
American publicly traded corporation, formerly McGraw Hill Financial, Inc
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