Senior Data Architect - AWS & Databricks Modernization

Job Summary

Senior Data Architect - AWS + Databricks Modernization at Scale

The Senior Data Architect (R5) is a hands-on Databricks and lakehouse modernization leader who owns the architecture and execution of large-scale migrations from legacy warehouses and point platforms onto a unified Databricks lakehouse for the Clinical and Non-Clinical data domain. This is a builder role: the architect writes code, builds migration pipelines, and personally ships production lakehouse assets - in addition to defining the modernization roadmap and rollout patterns that scale across dozens of domains. The role also owns the roadmap for semantic modeling and analytics-ready data, builds reusable data products the organization can adopt, drives data quality on clinical data specifically, and defines the metrics that enable data-driven decision making. AI-assisted and agentic ways of working are the expected default. Domain knowledge of the clinical data landscape is an added advantage. This role is split 70% hands-on technical execution including coding and 30% strategy, and shapes the future technology landscape.

Role

Key Responsibilities

• Lakehouse Modernization & Migration at Scale (Hands-On) - Own the technical roadmap and execution for migrating legacy warehouses, on-prem databases, and point data platforms onto Databricks - sequencing dozens of Clinical and Non-Clinical domains with minimal disruption.
• Personally build migration pipelines and re-platforming accelerators (schema conversion, historical backfill, dual-run validation, cutover automation) that move data at scale with parity and auditability.
• Define reusable modernization patterns - landing zone design, medallion (bronze/silver/gold) conventions, workspace/catalog topology - that scale consistently as new domains onboard.
• Right-size and standardize the Databricks platform footprint across environments (dev/test/prod, multiple workspaces) for cost, performance, and governance at enterprise scale.
• Establish cutover, rollback, and data-reconciliation practices that de-risk large-scale migrations in a regulated environment.
• Databricks Lakehouse Architecture & Engineering (Hands-On)
• Architect and build the Clinical/Non-Clinical lakehouse on Databricks, applying medallion design across Delta Lake tables at scale across multiple domains.
• This role is split 70% hands-on technical execution including coding and 30% strategy, and shapes the future technology landscape.

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