Manager, Business Systems Analyst
IQVIA · Barcelona
Central Automation CoE | IQVIA
Role Summary
Lead a team of Business Analysts within IQVIA's Central Automation CoE to deliver automation and AI value across multiple BUs and regions. Own portfolio management, people leadership, process/methodology stewardship, and project/delivery oversight. Ensure rigorous ADLC (AI/Automation Development Life Cycle) execution with Lean discovery, measurable ROI/FTE savings, and audit-ready documentation. Provide functional leadership for AI and agentic automation initiatives, including use-case discovery, solution feasibility, responsible AI considerations, human-in-the-loop controls, and business value realization.
Key Responsibilities
1 · Portfolio Management & Governance
- Own the BA portfolio across BUs/regions; manage intake via VIA/ServiceNow; maintain pipeline in Smartsheet; link Process IDs across Smartsheet, JIRA, and PSA.
- Partner with PMO on prioritization, capacity planning, and benefits tracking (ROI, FTE savings, cycle-time KPIs).
- Lead governance cadences: Weekly/Biweekly pipeline & delivery reviews, Monthly BU governance, and Quarterly sponsor reviews.
- Balance per-BA workload (~10-12 projects); resolve cross-team dependencies and bottlenecks.
2 · People Leadership
- Manage and coach BAs/Sr. BAs: goal-setting, performance management, feedback, and career development.
- Drive upskilling on Lean, ADLC, tools (Power Automate, Alteryx, Python/SQL) and GenAI/agentic technologies (Copilot, Cursor, LangGraph) including prompt engineering, retrieval-augmented generation (RAG), AI agent orchestration, AI-assisted requirements development, and responsible AI practices.
- Allocate resources effectively; support hiring, onboarding, and stretch opportunities.
- Foster a team culture of client focus, collaboration, ownership, and innovation.
3 · Process & Methodology (ADLC / Lean)
- Define and continuously improve BA standards, templates, and repositories (BRD, PDD, TFD, SDD; SharePoint/Confluence).
- Embed ADLC end-to-end: Intake → L0/L1/L2 Discovery → Technical Discovery → Business Case → Build → UAT → Rollout.
- Maintain RACI, single approval flow, prioritization criteria, and evidence-based traceability.
- Run retrospectives; sustain continuous improvement and team playbooks.
- Establish AI-specific BA standards covering problem framing, use-case suitability, prompt and knowledge-source requirements, model/agent evaluation criteria, human oversight, explainability, output validation, and post-deployment monitoring.
4 · Project & Delivery Oversight
- Assure discovery quality and gate readiness; lead Go/No-Go decisions with clear acceptance criteria.
- Oversee RAID management, change control (Major >16 hrs / Minor <16 hrs via VIA/ServiceNow), and compliance requirements.
- Align environments, access, data security, and governance with Architects and PMO.
- Ensure user stories, non-functional requirements, and traceability matrices are complete and testable.
- For AI solutions, ensure requirements address data and knowledge-source quality, hallucination and accuracy risks, prompt security, access controls, human-in-the-loop review, evaluation metrics, and responsible AI governance.
5 · Business Analysis & Solution Enablement
- Drive robust business cases (effort, FTE, ROI, payback period) with PMO/Finance inputs via PSA.
- Produce current/future-state process maps and L0/L1/L2 assessments; validate automation feasibility and value.
- Support tool selection (RPA/Power Automate, Alteryx, Python/SQL, OCR, GenAI); assess API/GUI integrations.
- Translate business needs into AI-ready requirements, including user journeys, prompt workflows, knowledge and data requirements, grounding/RAG needs, agent roles, orchestration logic, exception handling, human approval points, and measurable evaluation criteria.
- Assess the suitability of deterministic automation, predictive AI, generative AI, and agentic AI approaches based on process complexity, data availability, risk, scalability, and expected business value.
- Maintain full traceability from BRD/PDD through test coverage and production KPIs.
6 · Stakeholder Engagement & Communications
- Build trusted relationships with BU leaders, SMEs, Architects, and development teams across global time zones.
- Facilitate workshops, executive readouts, and governance forums; manage expectations and escalations.
- Standardize portfolio/delivery reporting (Power BI); champion CoE ways of working.
- Drive benefits realization tracking and coordinate smooth handovers to operations.
Required Qualifications
- Bachelor's degree in Business, Information Systems, Engineering, or related field
- 6-8+ years in Business/Systems Analysis, Automation, or Digital Transformation
- 3+ years leading Business Analysts or cross-functional delivery teams
- Proven end-to-end ADLC delivery: Intake → L0/L1/L2 → BRD/PDD → UAT → Rollout
- Portfolio oversight with PMO: prioritization, capacity, governance, value realization
- Delivery fundamentals: planning, RAID, change control in Agile/hybrid environments
- Lean-trained BA; process modeling (BPMN/Visio); benefits modeling; data-driven decisions
- Tooling: VIA/ServiceNow, Smartsheet, JIRA, PSA, SharePoint; Power BI
- Technical fluency: Power Automate/RPA, Alteryx, Python, SQL, OCR, GenAI/agentic tools
- Practical AI business analysis capability, including GenAI use-case discovery, prompt engineering, RAG and knowledge-grounding concepts, AI agent workflows, human-in-the-loop design, AI output evaluation, and responsible AI considerations.
Preferred Qualifications
- Experience in Automation processes or teams, Shared Services, Operational Excellence, or consulting environment; multi-region delivery.
- Finance or Life sciences or healthcare industry exposure.
- Automation Anywhere, SAP, PSFT, Azure/Databricks, and enterprise integration (API/GUI) experience.
- ITIL, data security, and governance awareness.
- Proven executive stakeholder management and executive-ready communications.
- Experience defining business and functional requirements for GenAI or agentic AI solutions using platforms or frameworks such as Microsoft Copilot, Azure AI, Cursor, LangGraph, or equivalent enterprise AI technologies.
- Understanding of AI solution risks and controls, including hallucination, bias, data privacy, prompt injection, secure grounding, explainability, human oversight, and model or agent performance monitoring
Preferred Certifications
- Lean Six Sigma - Green Belt or higher (Strongly Preferred)
- CBAP (Certified Business Analysis Professional) or PMI-PBA - Preferred
- PMP (Project Management Professional) or PRINCE2 Practitioner - Preferred
- Agile Certifications (Scrum Product Owner and/or Scrum Master) - Preferred
- ITIL Foundation - Plus
- Microsoft Power Platform Certifications (PL-900 and/or PL-200) - Plus
- Alteryx Designer Core or Automation Anywhere Certification - Plus
- Microsoft Copilot, Power Platform AI Builder, or equivalent Generative AI / Agentic AI Certification - Plus
Key Competencies
- Client Focus & Stakeholder Partnership
- Collaboration & Cross-functional Influence
- Clear, Concise Written & Verbal Communication
- Innovation & Continuous Improvement
- Ownership & Accountability
- Business Leadership & Strategic Thinking
- People Leadership & Coaching
- Adaptability, Flexibility, Organization & Planning
- AI Use-Case Discovery & Value Assessment
- Prompt Engineering & AI Requirements Definition
- Responsible AI, Risk & Governance Awareness
Experience Profile
The ideal candidate is a proven manager of BA teams delivering automation and AI solutions within an enterprise CoE. They manage a cross-BU/regional portfolio through ADLC and Lean practices — from intake through rollout and benefits realization. Skilled in governance cadences, financial/benefits tracking, and compliance in regulated environments, this leader remains hands-on in discovery and requirements quality while providing portfolio and delivery oversight. The candidate also brings practical AI acumen, with the ability to identify appropriate GenAI and agentic AI use cases, define AI-ready business and functional requirements, evaluate solution outputs against measurable criteria, and embed responsible AI, human oversight, data protection, and governance controls throughout the delivery lifecycle.
IQVIA is a leading global provider of clinical research services, commercial insights, and healthcare intelligence to the life sciences and healthcare industries. We create intelligent connections to accelerate the development and commercialization of innovative medical treatments to help improve patient outcomes and population health worldwide. Learn more at https://jobs.iqvia.com.
IQVIA is committed to integrity in our hiring process and maintains a zero tolerance policy for candidate fraud. All information and credentials submitted in your application must be truthful and complete. Any false statements, misrepresentations, or material omissions during the recruitment process will result in immediate disqualification of your application, or termination of employment if discovered later, in accordance with applicable law. We appreciate your honesty and professionalism.
At IQVIA, we believe that diversity, inclusion, and belonging empower our mission to accelerate innovation for a healthier world. We create a culture of belonging by valuing the perspectives of all talented employees worldwide and providing them with the opportunity to power smarter healthcare for everyone, everywhere. When our talented employees bring their authentic selves and their diverse experiences to work, they enable us to accomplish extraordinary things. Multifaceted thought processes spark innovation. Multi-talented collaboration harnesses innovation to deliver superior outcomes. Likewise, as part of this culture, IQVIA is committed to ensuring effective equality between women and men, integrating it as a strategic principle in its corporate and human resources policies.