Director II, Data Engineering - Business Technology Solutions

Company Description

About Abb Vie

Abb Vie's mission is to discover and deliver innovative medicines and solutions that solve serious health issues today and address the medical challenges of tomorrow. We strive to have a remarkable impact on people's lives across several key therapeutic areas including immunology, oncology and neuroscience - and products and services in our Allergan Aesthetics portfolio. For more information about Abb Vie, please visit us at  Follow @abbvie on Linked In, Facebook, Instagram, Xand You Tube.

We are seeking a senior leaderforthe

Data Engineering team supporting the Development side of R&Dwithin Abb Vie's Information Research organization. This role is accountable for the ingestion, curation, integration, quality, and reliable delivery of the transactional data that supports Abb Vie's drug development pipeline from first-in-human clinical trials through medical affairs. The leader will partner across Clinical Operations, Portfolio Performance and Business Excellence,Finance, Statistics, Regulatory Affairs, CMC, Drug Supply, Data Management,Pharmacovigilance, Medical Health Impact,Quality, and Compliance to ensure trusted, governed, fit-for-purpose data is available for operational execution, analytics, reporting,integrations and decision-making.

The role will lead approximately 15 Abb Vie engineers and oversee close to 100 contractors from a strategic partner, combining technical depth, delivery discipline, and enterprise leadership to scale a modern, reliable development data engineering capability.

Development Data Engineeringoperatesacross a complex, regulated, and highly interconnected data landscape consisting of both internal source systems and external partners supporting the drug development pipeline. This role is accountable for turning that complexity into trusted, well-governed, reusable data assets that improve interoperability, strengthen data quality and lineage, reduce operational friction, and accelerate data-driven decisions across the drug development lifecycle.

Responsibilities:

• Own the Development Data Engineering vision , strategy, and multi-yearroadmap;align ingestion, curation, integration, and data quality priorities with
  
  Information Research,enterprise architecture, business stakeholders, regulatory expectations, and investment priorities.
• Define the operating model for Development Data Engineering, including intake and prioritization, design standards, delivery governance, data quality controls, release discipline, production support, decision rights, and accountability across Abb Vie engineers, strategic partner contractors, business partners, and platform teams.
• Lead and develop a high-performing organization of approximately 15 Abb Vie data engineers while providing day-to-day leadership, accountability, and delivery oversight for nearly 100 strategic partner contractors; build engineering capability, talent depth, partner performance discipline, and a culture of quality, ownership, and continuous improvement.
• Shapeportfolioand investment decisions by translating data engineeringtradeoffs into business value,delivery risk,compliance impact, operational resilience, and total cost; influence prioritizationacrosspipelinedata platforms,integration capabilities,modernization efforts, partner capacity, and quality improvements.
• Provide engineering leadership for major development data initiatives, including platform modernization, transactional data ingestion, data product creation, integration pattern standardization, lineage and metadata foundations, data quality automation, operational monitoring, and simplification of duplicative capabilities.
• Design and govern target-state patterns for development data platforms, transactional data pipelines, curated data products, integration services, metadata and semantic layers, master and reference data, data quality controls, observability, access management, and audit-ready delivery in a regulated environment.
• Define cross-cuttingengineeringstandards for schema design,metadata management, data lineage, masterand reference data, interoperability, APIand integration patterns,semantic consistency, security, encryption, access control, resiliency,observability, data quality, and compliance evidence.
• Establish and chairengineeringgovernance forums to ensure consistent design, delivery discipline, production readiness, data quality accountability, compliance alignment,disciplined exception management, and scalable reuseacrossdevelopment…