Microsoft-focused software development and data engineering for financial services
SoHo Dragon is a Microsoft application stack specialist with deep financial services expertise, built around Azure, Power BI, and data-pipeline tools (dbt, Spark, Snowflake, Redshift). The company's project list centers on Murex implementation and trading workflows—indicating a concentrated vertical in capital markets—while the tech stack spans both traditional BI (Tableau, Looker, Power BI) and modern data engineering (Databricks, Synapse, dbt). Hiring velocity is accelerating across technical and operational roles, with a seniority skew toward senior-level placements.
SoHo Dragon is a full-service software development firm headquartered in New York and founded in 2010, serving mid-market and enterprise clients primarily in financial services and construction. The company operates three business lines: project-based application development (portals, document management, CRM, business intelligence), staff augmentation, and direct placement services. Work is predominantly built on the Microsoft technology stack—SharePoint, Azure, Power BI, SQL Server—alongside modern data tools like Databricks and Snowflake. The client base includes organizations managing high-complexity workflows in trading, market data, KYC, and tax operations.
Primary: Azure (Data Factory, Synapse, Data Lake, Blob Storage), Power BI, SQL, Python, dbt, Spark. Also: Snowflake, Redshift, Tableau, Looker, Murex, Databricks, Alteryx, Jira.
Murex implementations and upgrades, trade workflow development, market data management systems, operating model transformation, and KYC/client onboarding review automation for financial services clients.
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SoHo Dragon's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.