Specific skills/other requirements - Experience must include (quantitative experience requirements not applicable to this section): Engineering data lake, lakehouse, data warehouse, or data mesh environments on AWS using secure and scalable design patterns; implementing platform engineering with reusable infrastructure, automation, IaC, and CI/CD for data platforms; developing and managing Databricks solutions for data engineering, Machine Learning (ML) workflows, and AWS integrations (S3, Glue, and Redshift); utilizing AWS native tools and serverless technologies, including IAM, KMS, Lake Formation, Lambda, CloudFormation, and Step Functions to develop data platforms; applying cloud security best practices within multi-account environments, including access control, encryption, and auditability; and, containerizing and orchestrating applications using Kubernetes in cloud-native deployments. Requires: Master's degree in Computer Engineering, Computer Science, Information Technology Management or related field (willing to accept foreign education equivalent) plus three (3) years of experience as an AWS Cloud Platform Engineer or related role building and automating secure, scalable cloud data platforms in the finance or insurance industry or, alternatively, a bachelor's degree in Computer Engineering, Computer Science, Information Technology Management or related field (willing to accept foreign education equivalent) plus five (5) years of experience as an AWS Cloud Platform Engineer or related role building and automating secure, scalable cloud data platforms in the finance or insurance industry.