Associate Director, Data Engineering - (Contract)

Role Summary The Associate Director, Data Engineering owns the data architecture, quality, and integration backbone connecting the platform to the client's system-of-record landscape (MDM, ERP, and third-party enrichment sources) and to downstream reporting/analytics. This role leads a data engineering team responsible for resolving persistent data-quality and system-sync defects and building the reporting layer that supports SLA, cycle-time, and forecast-accuracy metrics. This engagement uses an agent-orchestrated development model, so hands-on AI-assisted development experience is required here as well. Note: This role is 20 hours per week work. Key Responsibilities Own the data architecture strategy connecting the CRM/onboarding platform, MDM, and ERP systems, ensuring a single, trusted flow of customer and account data across systems. Lead resolution of data-integrity defects: field mapping mismatches, cross-system sync gaps, and data carryover issues between intake and downstream systems. Design and govern the data validation/enrichment pipeline integrating third-party sources, prioritizing API-based integration over manual/portal workflows where feasible. Own the data model and pipeline design supporting AI-driven document data extraction and validation feedback loops. Build and lead the reporting/analytics data layer covering cycle time, SLA adherence, bottleneck identification, queue prioritization impact, data completeness/validation error rates, and forecast accuracy vs. actual go-live dates. Lead data governance for sensitive data flows (e.g., PHI) in coordination with the client's compliance and security teams. Direct and leverage AI coding agents (e.g., Claude Code or equivalent) for pipeline development, data validation logic, and rapid prototyping of integration fixes. Manage and grow a team of data engineers/analysts; set technical standards for data pipeline development, testing, and monitoring. Partner with the Principal Architect and Solution Architect to ensure data model decisions are compatible with downstream MDM, ERP, and reporting requirements. Present data quality, integration health, and reporting-accuracy findings to program leadership and client stakeholders as needed. Required Qualifications 12+ years in data engineering/architecture roles with 5+ years leading data engineering teams in an enterprise transformation context. Proven experience designing and troubleshooting data integrations between CRM, ERP, and master data management platforms. Strong background in data quality remediation — field mapping, sync architecture, and batch/real-time integration defect resolution at enterprise scale. Experience building reporting/analytics pipelines supporting operational metrics for business stakeholders. Hands-on experience directing or prompting AI coding agents (e.g., Claude Code or an equivalent agentic development tool) as part of an agent-orchestrated delivery model — required. People-management experience leading a data engineering team through concurrent, high-stakes delivery streams. Familiarity with PHI/regulated data handling requirements and working alongside compliance/security teams. Preferred Qualifications Experience with enterprise integration/middleware platforms. Background in pharmaceutical distribution, healthcare, or GPO/rebate data models. Familiarity with AI/LLM-based data extraction pipelines. Relevant data architecture or platform-specific data management certifications.