Data Quality / Profiling Analyst (Sr Consultant Level)

DataCatalyst is a specialized consulting firm that empowers enterprises to leverage their data as a strategic asset. The company focuses on three core pillars: data management, data governance, and data monetization. With a team of seasoned experts who average over 15 years of experience, DataCatalyst prides itself on a 100% project success rate, often being engaged to rescue and revitalize data initiatives that have previously failed. The firm caters to a diverse range of industries, including manufacturing and distribution, financial services, healthcare, retail, energy, publishing, telecommunications, and transportation. By bridging the gap between business and technology, DataCatalyst delivers solutions that enhance data quality, streamline processes, and drive tangible business value. The company’s proprietary 'Accelerate' methodology provides a structured and efficient path to achieving high-quality, centralized data that supports an organization's strategic mission.

Operating on a global scale with a distributed team, DataCatalyst maintains a significant presence in North America and Europe, with headquarters in New York and London. This model allows the firm to provide responsive, worldwide service without the overhead of physical offices, reflecting the global nature of its enterprise clientele. DataCatalyst's approach is hands-on and pragmatic, eschewing large teams of junior consultants in favor of lean, highly skilled 'SWAT' teams tailored to each engagement. The firm collaborates with a curated selection of best-in-class technology partners, including leaders in Master Data Management (MDM), Product Information Management (PIM), data governance, and cloud services. This technology-agnostic approach ensures that clients receive customized strategies and implementations that maximize their return on investment. By focusing on creating a data-driven culture where information is trusted and accessible, DataCatalyst helps organizations eliminate inefficiencies, improve decision-making, and unlock new revenue streams from their data assets.