Senior Data Lakehouse Architect; Databricks), Vice President

Senior Data Lakehouse Architect (Databricks), Vice President Corporate Functions Technology Who We Are Looking For We are seeking a Senior Data Lakehouse Architect to design and lead the build-out of a Legal Data Lakehouse platform on AWS and Databricks. This role will drive the architecture, engineering, and governance of scalable, secure, and compliant data capabilities supporting legal operations, contract intelligence, eDiscovery, and AI/ML use cases.

The ideal candidate brings deep expertise in Databricks, AWS data platforms, and enterprise data architecture, with experience delivering solutions in regulated environments aligned to security, compliance, and audit requirements.

Why This Role Is Important to UsState Street’s Legal function operates across a broad set of contracts, matters, regulatory obligations, documents, and workflows that are distributed across multiple systems and formats. Building a modern Legal Data Lakehouse is critical to creating a trusted, governed foundation that brings these data sources together—making legal information easier to access, analyze, and use s role is critical to establishing a secure and scalable data foundation that enables legal analytics and AI use cases while strengthening governance, auditability, and global consistency across Legal.

What You Will Be Responsible For
1. Architecture & Platform Design Define and implement the end-to-end Legal Data Lakehouse architecture using Databricks (Delta Lake, Unity Catalog, Workflows) on AWSDesign multi-layered data architecture (Bronze, Silver, Gold) to support:

Contract metadata and document ingestion

Legal matter management datae

Discovery datasets

External regulatory and compliance feeds

Establish scalable ingestion frameworks (batch and streaming) for structured and unstructured legal data (PDFs, contracts, emails)2. Data Engineering & Integration Lead development of ETL/ELT pipelines using Databricks, Spark, and Python/SQLIntegrate with enterprise platforms, including:

Contract lifecycle management systems

AI platforms and LLM pipelines

Document repositories and enterprise content systems

Design patterns for extracting structured data from unstructured legal documents and persisting into Delta Lake Enable downstream integration with enterprise data platforms, analytics tools, and AI/ML pipelines
3. Governance, Security & Compliance Implement data governance frameworks using Databricks Unity Catalog and AWS-native controls (IAM, KMS)
Establish:

Fine-grained access controls (row/column-level security)
Data lineage and auditability

Ensure compliance with:

Data privacy regulations (e.g., GDPR)
Internal security and audit requirements

Partner with IAM teams to integrate with enterprise identity providers (e.g., Entra  / Azure AD)4. AI/ML & Advanced Analytics Enablement Architect data models supporting:

Contract analytics, clause extraction, and obligation tracking

Legal AI use cases (contract review, litigation insights, compliance monitoring, legal spend analytics)
Design search and retrieval architectures (RAG) for enterprise legal knowledge bases

Enable entity extraction and knowledge graph frameworks

Integrate with LLM/GenAI platforms to support capabilities such as document summarization, Q&A, and workflow automation
5. Dev Ops & Platform Operations Establish CI/CD pipelines and infrastructure-as-code (Terraform, Git-based workflows)
Define standards for:

Code quality and versioning

Environment promotion (Dev / QA / Prod)
Implement observability and alerting for platform health and reliability
6. Leadership & Stakeholder Engagement Partner with Legal and Technology leadership to define platform roadmap and priorities

Provide architectural governance and design oversight

Mentor data engineers and platform teams

Translate business and legal requirements into scalable, enterprise-grade solutions

Operate within a federated data and platform model, collaborating across engineering, security, and domain teams

What We Value The skills that will help you succeed in this role include:10+ years of experience in data architecture, engineering, or analytics platforms5+ years of hands-on experience with Databricks and Apache Spark Strong…