Data Solutions Architect (Full-Onsite)

Insight Global is hiring an Experienced Data Solutions Architect top financial services client within Equities Technology. This role focuses on building enterprise data architecture and business ready domain models supporting investment banking, equities, and wealth management. You’ll partner with business teams to define data domains and work with engineers to model trusted data in a Databricks lakehouse, supporting platforms like DealCloud, Power Apps, and Salesforce. Ideal candidates bring strong business acumen with hands on experience in data modeling, SQL, Python, and modern analytics tools.

Day-to-day:

• Partner with bankers, business leaders, and senior stakeholders to capture workflows, entities, and requirements
• Design and maintain logical and semantic data models aligned to enterprise architecture
• Define attributes, hierarchies, and business rules for core domains (funds, sponsors, deals, coverage, etc.)
• Explore, validate, and transform datasets using SQL, Python, and Databricks
• Shape raw data into business-ready domain tables
• Prototype pipelines and transformations before handing off to engineering for production
• Collaborate with internal and external CRM teams to support data decisions in DealCloud and Salesforce
• Present data models and findings to stakeholders and iterate based on feedback
• Act as a trusted bridge between business stakeholders and technical teams

Requirements:

• 4-7 years of experience in data modeling, data architecture, or data solution design
• Strong hands-on experience with: SQL, Python, Databricks or similar modern data platforms
• Deep understanding of logical & semantic data modeling, Data semantics, ontologies, and master data management (MDM)
• Experience working in financial services or consulting
• Ability to translate business requirements into data models
• Strong communication skills with both technical and non-technical stakeholders

Compensation:

$75- $90 per hour

Exact compensation may vary based on several factors, including skills, experience, and education.