RGP is hiring a Director, Data Platform & Integration to help grow and deliver work across our Digital Build & Integration practice. This person will drive sales, serve as the solution architect for data platform and integration opportunities, and provide technical leadership through delivery. The right candidate brings senior-level depth across the full enterprise data lifecycle and the consulting experience to turn complex, cross-platform data challenges into solutions that can be sold, scoped, built, and expanded. They operate with a system-level perspective from ingestion and integration through modeling and consumption, and they carry that perspective into every client conversation. This is a client-facing role for someone who can move fluidly between architecture-level conversations with enterprise data architects and business-level conversations with CIOs, CDOs and data platform owners, independently shape engagements, and stay accountable for technical quality once the work is sold. Base Pay Range: $170,000 - $213,000 Other Compensation: Incentive Compensation + Drive new and expanded client work for the practice, with a focus on data platform, Master Data Management, and enterprise integration engagements. + Build relationships with senior client stakeholders including CDOs, enterprise architects, VPs of Data, and data platform owners across financial services, healthcare, and enterprise accounts. + Lead technical sales conversations from discovery through solutioning, proposal, close, delivery, and expansion, operating as the primary technical voice in pursuit situations. + Serve as the solution architect for data platform and integration engagements, owning the technical approach from first conversation through delivery. + Define architecture direction, platform fit, integration strategy, operational data model design, assumptions, risks, and pricing inputs across environments including Databricks, Snowflake, Azure Data Factory, Microsoft Fabric, and Azure Data Lake. + Bring a system-level perspective across the full data lifecycle, including ingestion, orchestration, integration, MDM, service-layer architecture, modeling, and consumption, to ensure solutions are coherent end to end and not just technically competent in isolation. + Translate complex, cross-platform data challenges into clear solution paths that CDOs, enterprise architects, and business stakeholders can understand, evaluate, and commit to. + Create and present proposals, estimates, solution narratives, executive recommendations, technical approaches, and delivery recommendations. + Provide technical leadership during delivery, including architecture decisions, solution direction, technical risk management, and quality of outcomes. + Guide delivery team members on technical approach and platform standards, stepping in to resolve architecture-level issues that affect scope, feasibility, or client confidence. + Use AI-native development approaches to rapidly explore, prototype, and validate solutions, converting ambiguous client needs into executable, high-value work faster than traditional discovery and design cycles allow. + Identify expansion opportunities through strong delivery, client trust, and a clear understanding of the client's broader data ecosystem needs. + Build reusable sales assets, solution frameworks, demos, estimation models, and delivery approaches that strengthen the practice's ability to pursue and close data platform work. + 10+ years of experience designing and delivering enterprise data platform solutions, including data pipelines, MDM implementations, service-layer integrations, and cloud data migrations. + 10+ years of experience in a professional services, consulting, systems integration, or client-facing delivery environment. + Deep, hands-on technical expertise across the full data lifecycle, with specific platform depth in two or more of the following: Databricks, Azure Data Factory, Snowflake, Microsoft Fabric, and Azure Data Lake. + Strong command of enterprise MDM patterns, service-layer integration architecture, and operational data model design in complex, multi-system environments. + Demonstrated ability to operate with a system-level perspective across ingestion, orchestration, modeling, and consumption layers, with the judgment to identify where architectural decisions in one layer create risk or constraint in another. + Proven ability to drive technical sales conversations independently with CDOs, enterprise architects, and data platform owners, including diagnosing the real problem, framing a solution, and advancing the opportunity through to close. + Comfortable moving between technical depth and business language in the same conversation, adjusting altitude without losing credibility at either level. + Track record of delivering large-scale data platform programs end-to-end with the delivery experience to know what makes an architecture realistic versus aspiration