Data Engineering Director

RGP•Chicago, IL

3d•$170,000 - $213,000•Remote

About The Position

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.

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.

Nice To Haves

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.

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.