Senior Data Disposition & Migration Intelligence Engineer

We use cookies to offer you the best possible website experience. Your cookie preferences will be stored in your browser’s local storage. This includes cookies necessary for the website’s operation. Additionally, you can freely decide and change any time whether you accept cookies or choose to opt out of cookies to improve website’s performance, as well as cookies used to display content tailored to your interests. Your experience of the site and the services we are able to offer may be impacted if you do not accept all cookies. Modify Cookie Preferences Accept All Cookies Search Jobs, Senior Data Disposition & Migration Intelligence Engineer Key Skills Required Must-have (prioritize candidates with depth in these areas): Priority Skills Critical - Amazon Bedrock - model selection, prompt design, Knowledge Bases, retrieval-augmented generation (RAG), guardrails, and production inference patterns Critical - AWS platform - CI/CD (CodePipeline / GitHub Actions on AWS), Lambda, Step Functions, OpenSearch (vector search), Neptune or graph storage, Secrets Manager, S3 artifact pipelines, IAM, and cost/scale design Required SQL Server at scale - stored procedure dependency tracing, cross-database schema reconciliation, RLS / SESSION_CONTEXT Dispositioning & triage - turning automated outputs (schema drift, source-only tables, static-analysis findings) into auditable, dependency-backed decisions ID de-collision analysis - overlapping ID ranges, true collisions vs. co-mingled data, table-level resolution ETL / batch consolidation - Informatica (or equivalent), migration script quality, tenant-scoped batch jobs LLM output validation - guardian / evaluation patterns, golden-set regression, confidence thresholds Code literacy (.NET, Java, Angular, Python); static analysis & SARIF; financial-services consolidation experience

Senior practitioner who combines deterministic data engineering with Bedrock-powered AI reasoning to accelerate a large-scale multi-tenant consolidation. You turn automated signals - schema drift, source-only tables, ID collisions, and static-analysis findings - into defensible disposition decisions grounded in dependency chains (stored procedures, application code, ETL, batch jobs). You also productionize the toolchain on AWS: RAG through CI/CD, knowledge capture, and a guardian pattern that validates every model output before it reaches reviewers or migration teams., Required 8+ years in data engineering, platform migration, or enterprise modernization (financial services preferred). Production experience with Amazon Bedrock and core AWS services (not exploratory POCs). Large-scale SQL Server dependency analysis and schema reconciliation. Hands-on ETL/batch consolidation (Informatica or equivalent). CI/CD integration and LLM output validation in production workflows. Preferred Multi-tenant consolidation, tenant discriminators, feature entitlements. Code graph / static analysis (Roslyn, OpenRewrite, CodeQL, custom analyzers). Guardian patterns for LLM outputs; Python/PowerShell report pipeline automation. Mandatory Skills: Data Analysis . Experience: 5-8 Years .

The expected compensation for this role ranges from $60,000 to $135,000 .

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