Data Architect

We are seeking an experienced Data Architect to help design and scale a modern enterprise data platform supporting multiple lines of business, including investment banking, capital markets, and wealth management.

This is a highly visible, hands-on role focused on enterprise data architecture, domain modeling, and delivering trusted, business-ready data
. You will work closely with business stakeholders, data engineers, and analytics teams to translate real-world workflows into scalable data models that power reporting, analytics, and downstream applications.

The ideal candidate blends strong business acumen with deep technical expertise across data modeling, SQL, Python, and modern cloud data platforms.

• Partner directly with business stakeholders to understand workflows, entities, and data requirements
• Design and maintain logical, semantic, and domain-driven data models aligned to enterprise architecture standards
• Define core data domains, attributes, hierarchies, and business rules (e.g., deals, funds, clients, sponsors, coverage)
• Translate business requirements into well-structured, scalable data models for analytics and operational use
• Collaborate with data engineers on ingestion, transformation, and enrichment pipelines
• Explore, validate, and shape datasets using SQL, Python, and Databricks
• Prototype data transformations and pipelines, then partner with engineering teams for production deployment
• Ensure data is accurate, mastered, governed, and consumable across downstream systems (e.g., CRM, analytics tools, internal applications)
• Present data models and architectural decisions to technical and non-technical stakeholders
• Act as a bridge between business users and technical teams, ensuring solutions are both practical and scalable

• 4–7 years of experience in data architecture, data modeling, solution design, or hybrid data/business roles
• Strong experience within financial services, consulting, or enterprise data environments
• Hands-on expertise with:
• Python (data wrangling, prototyping, APIs, PySpark preferred)
• Databricks or comparable cloud data platforms
• Deep understanding of:
• Master Data Management (MDM) and data governance principles
• Modern data integration patterns (ETL/ELT, APIs, third-party data sources)
• Strong communication skills with the ability to translate complex data concepts to business audiences
• Highly organized, proactive, and comfortable balancing big-picture architecture with hands-on execution

• Direct exposure to senior business and technology stakeholders
• Opportunity to work with modern cloud data technologies
• A mix of strategic design and hands-on problem solving