Company Description

About AbbVie

AbbVie'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 AbbVie, please visit us at www.abbvie.com. Follow @abbvie on LinkedIn, Facebook, Instagram, X and YouTube.

Job Description

We are seeking a senior leader for the Data Engineering team supporting the Development side of R&D within AbbVie's Information Research organization. This role is accountable for the ingestion, curation, integration, quality, and reliable delivery of the transactional data that supports AbbVie'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 AbbVie 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 Engineering operates across 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-year roadmap; 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 AbbVie engineers, strategic partner contractors, business partners, and platform teams. 
• Lead and develop a high-performing organization of approximately 15 AbbVie 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. 
• Shape portfolio and investment decisions by translating data engineering tradeoffs into business value, delivery risk, compliance impact, operational resilience, and total cost; influence prioritization across pipeline data 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-cutting engineering standards for schema design, metadata management, data lineage, master and reference data, interoperability, API and integration patterns, semantic consistency, security, encryption, access control, resiliency, observability, data quality, and compliance evidence. 
• Establish and chair engineering governance forums to ensure consistent design, delivery discipline, production readiness, data quality accountability, compliance alignment, disciplined exception management, and scalable reuse across development data initiatives. 
• Drive data governance, compliance, privacy, and risk management in partnership with Legal, Security, Privacy, and Compliance teams, ensuring architectures support regulated use cases and audit readiness. 
• Guide enterprise tooling and partner strategy for data engineering activities; evaluate strategic vendors, influence sourcing decisions, and oversee complex proof-of-concept and due diligence efforts tied to long-term capability building. 
• Represent data engineering architecture strategy in executive forums; communicate options, risks, investment tradeoffs, and transformation implications to senior leadership in business terms. 
• Contribute to financial stewardship for a large-scale architecture and transformation portfolio, including shaping annual and multi-year investment plans, cost discipline, and value realization expectations. 
• What success looks like:
  • Enterprise adoption of a clear target-state architecture, standards, and decision framework across business units, products, and delivery teams 
  • Measurable reduction in fragmented platforms, duplicated capabilities, and architectural exceptions across the R&D landscape 
  • Improved speed to deliver data through reusable patterns, stronger interoperability, and simplified architecture governance. 
  • Demonstrable business value from major transformation investments, including cost optimization, capacity efficiency, risk reduction, and improved delivery predictability. 
  • Mature enterprise architecture practice with strong bench strength, documented patterns, disciplined governance, and visible influence on executive investment choices 

Qualifications

Required:

• Bachelor’s Degree in Computer Science, Engineering, or related field with 12+ years of experience.
• Proven success building and leading high performing teams of both solid line and matrixed reporting structures. 
• Strong experience shaping roadmaps, target-state architectures, and major investment decisions tied to modernization, simplification, and scale. 
• Proven success designing Data architectures including data products, feature stores, monitoring, and governance in regulated environments. 
• Demonstrated ability to influence senior executives and cross-functional leaders by translating complex technical choices into business value, risk, and financial implications. 
• Experience establishing enterprise governance mechanisms, architecture review processes, standards adoption models, and operating rhythms across diverse teams. 
• Strong financial and strategic acumen, including experience informing portfolio prioritization, investment planning, vendor strategy, and value realization discussions. 
• Behaviors & leadership expectations:
  • Enterprise executive who balances long-range strategic vision with pragmatic delivery and sustained adoption 
  • Leader of leaders who builds organizational capability, develops senior talent, and scales influence through strong leadership teams. 
  • Highly credible partner to business and technology executives, able to simplify complexity and shape critical decisions through trust and clarity. 
  • Disciplined steward of investment and risk who advances innovation while driving accountability, resilience, and value realization. 

Preferred:

• Advanced degree (MS/PhD) in Computer Science, Engineering, or related field 
• Prior experience as an enterprise architect or head of architecture in a data/AI-intensive organization 
• Background in regulated industries and familiarity with compliance frameworks and audit processes 
• 10+ years of progressive experience in software engineering, data engineering, enterprise architecture, or platform leadership, including significant experience influencing at scale in large, complex organizations. 
• 10+ years of building production grade data capabilities  
• Deep expertise in cloud architecture, distributed systems, enterprise data platforms, interoperability, and modern data ecosystem design 

Additional Information

Applicable only to applicants applying to a position in any location with pay disclosure requirements under state or local law: ​

• The compensation range described below is the range of possible base pay compensation that the Company believes in good faith it will pay for this role at the time of this posting based on the job grade for this position. Individual compensation paid within this range will depend on many factors including geographic location, and we may ultimately pay more or less than the posted range. This range may be modified in the future. ​

• We offer a comprehensive package of benefits including paid time off (vacation, holidays, sick), medical/dental/vision insurance and 401(k) to eligible employees.​

• This job is eligible to participate in our long-term incentive programs. ​

Note: No amount of pay is considered to be wages or compensation until such amount is earned, vested, and determinable. The amount and availability of any bonus, commission, incentive, benefits, or any other form of compensation and benefits that are allocable to a particular employee remains in the Company's sole and absolute discretion unless and until paid and may be modified at the Company’s sole and absolute discretion, consistent with applicable law.​

AbbVie is an equal opportunity employer and is committed to operating with integrity, driving innovation, transforming lives and serving our community.  Equal Opportunity Employer/Veterans/Disabled. 

US & Puerto Rico only - to learn more, visit https://www.abbvie.com/join-us/equal-employment-opportunity-employer.html

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