Digital transformation and tech staffing for financial services, healthcare, and government
Sharp Decisions is a 33-year-old digital transformation and staffing firm serving regulated verticals (financial services, healthcare, government). The tech stack reveals heavy data infrastructure work: Databricks, Azure data lake, Power BI, SQL Server, Python—with active migration to .NET and Playwright adoption. The project list (cybersecurity data lakehouse, system rewrites, row-level security, dashboard builds on Databricks) and pain-point clustering (data integration, compliance accuracy, governance) indicate Sharp Decisions is modernizing client infrastructure toward cloud data platforms while managing complex regulatory requirements.
Sharp Decisions provides digital transformation consulting, tech staffing, and managed services across financial services, healthcare, manufacturing, government, and media/telecom sectors. The firm operates through three main service lines: talent acquisition (V.E.T.S. program), consulting (D-Sharp.io), and project delivery. With offices across the U.S. and nearshore/offshore capabilities, the company combines technologists and industry experts to handle large-scale system migrations, data infrastructure builds, and compliance-heavy operational challenges. Current hiring velocity is accelerating, concentrated in engineering, data, and ops roles at senior and mid levels.
Manhattan WMS, Databricks, Azure Data Lake Storage, Power BI, SQL Server, Python, Java, Jenkins, Docker, Kubernetes, GitLab, Ansible. Currently adopting .NET and Playwright; no active replacements in top stack.
Building cybersecurity data lakehouses, migrating systems to .NET, implementing row-level security and data governance, developing dashboards on Databricks/Azure, and onboarding new financial providers and clearinghouses.
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Sharp Decisions'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.