Data Architect

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• Database Migration Design & Execution: Design and execute migrations of relational databases (Oracle, SQL Server, PostgreSQL) to AWS, including Aurora PostgreSQL, Amazon RDS and Oracle Database@AWS. \n

• Schema & Code Conversion: Perform schema and PL/SQL conversion and refactoring, including heterogeneous Oracle to PostgreSQL migrations, using AWS Schema Conversion Tool (SCT) and AWS Database Migration Service (DMS). \n

• Migration Waves: Plan and run migration waves end-to-end: assessment, cutover, data validation and post-migration performance tuning. \n

• Target-State Data Architecture: Produce target-state data models, migration runbooks, architecture decision records (ADRs) and guidance for application teams. \n

• Security & Compliance: Ensure migrated databases meet security and compliance requirements, applying least-privilege IAM and AWS KMS encryption at rest and in transit. \n

• Automation: Use Python and Terraform to automate data processing, migration tasks and database infrastructure provisioning. \n

• Agile Delivery: Manage your own user stories in Jira within the sprint and collaborate closely with application, infrastructure and cloud engineering teams. \n

We are seeking a Senior Data Architect to join our AWS practice and work embedded with AWS Professional Services (ProServe) teams, modernizing a large, legacy relational database estate on AWS for a major financial services institution. You will lead the migration and modernization of complex Oracle, SQL Server and PostgreSQL workloads to AWS, primarily to Amazon Aurora PostgreSQL and, where applicable, Oracle Database@AWS (ODB@AWS), covering schema and PL/SQL conversion, migration waves, cutover and validation. The ideal candidateis a hands-on database expert with deep relational and SQL skills, a proven record of production database migrations to AWS, and the ability to guide application teams through target-state design., * Relational Databases: Expert-level (Level 400), hands-on experience with at least two of Oracle,SQL Server and PostgreSQL, with advanced SQL and PL/SQL. \n

• Database Migration to AWS: Proven delivery (Level 300-400) migrating production databases to Aurora PostgreSQL and/or Amazon RDS using AWS DMS and AWS SCT. \n

• Core AWS Data Stores: Hands-on experience (Level 300) with Amazon RDS, Aurora PostgreSQL, S3, IAM and KMS. \n

• Documentation: Ability to write clear target-state data models, migration runbooks and ADRs for technical and risk audiences. \n

• AWS Certification: Active AWS Certified Solutions Architect - Associate(required); Professional preferred. \n, * Consulting: Prior experience with AWS ProServe or in a consulting delivery role.

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• Python: Python for data processing and migration automation. \n

• PL/SQL Conversion at Scale: Large-scale Oracle to PostgreSQL code conversion and heterogeneous migration experience. \n

• Oracle Database@AWS: Familiarity with ODB@AWS. \n

• Financial Services: Delivering financial services or other regulated enterprises, with awareness of PCI-DSS and SOC 2. \n

• Infrastructure as Code: Terraform(AWS CDK is not required). \n

• Agile / Jira: Comfortable managing your own user stories within a sprint (Level 200). \n

• Agentic AI Accelerators: Using Amazon Bedrock or agentic AI for data accelerators such as code analysis and conversion or data-domain tagging. This is a differentiator, not a requirement. \n

• DataLake & Lakehouse: Exposure to AWS Glue, Lake Formation, Athena and Amazon Redshift. \n

• Legacy Sources: Familiarity with Exadata, Sybase,DB2 or mainframe data sources. \n

• GenAI Developer Tools: Use of AI coding assistants such as Amazon Q Developer or Kiro.