Data Engineering Director

About the role

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.

Responsibilities

• 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.

Requirements

• 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 aspirational.
• Hands-on experience using AI-native tooling to accelerate data platform delivery work, including pipeline scaffolding, schema and model generation, integration documentation, or automated data quality validation.
• Prior delivery experience in financial services, healthcare, or other regulated industries where data governance, auditability, and compliance constraints shape platform and integration decisions is desirable.
• Familiarity with federated data governance models, data mesh architecture, or enterprise data product strategies as applied to large, multi-domain environments is also desirable.

Qualifications

• Master's degree in Computer Science, Information Systems, Business Administration, or related field.
• Professional certifications such as MCSE, MCSD, or similar relevant certifications.
• Experience with data warehousing, data modeling, and data architecture.
• Experience with cloud platforms like AWS, Google Cloud, or Azure.
• Experience with data integration tools and technologies.
• Experience with data governance and compliance frameworks.

Skills

• Strong analytical and problem-solving skills.
• Excellent communication and presentation skills.
• Ability to work effectively in a team environment.
• Ability to manage multiple projects simultaneously.
• Ability to lead and mentor junior staff.

Benefits

• Medical, Dental, Vision, Life Insurance, Disability Insurance.
• 401(k) Savings Plan.
• Employee Stock Purchase Plan.
• Professional Development Program.
• Paid Time Off.
• Paid Holidays and Paid Sick Time (in geographies where legally required).

Pay

Base Pay Range: $170,000 - $213,000

Schedule

Full-time