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# Manager, Business Systems Analyst

- **Company:** IQVIA
- **Location:** Barcelona, Spain
- **Contract:** Permanent contract
- **Skills:** LangGraph Framework, Microsoft Access, Application Programming Interfaces (APIs), Agile Methodology, Artificial Intelligence, Optical Character Recognition (OCR), Confluence, JIRA, Microsoft Azure, Business Process Model and Notation, Business Systems, Code Coverage, Information Systems, Data Security, Cursor, RAID, Systems Analysis, Intrusion Detection Systems, Python (Programming Language), Microsoft Visio, PRINCE2, Scrum Methodology, Power BI, Microsoft Copilot, Robotic Automation Software, SAP (Applications), Microsoft SharePoint, Software Requirements Analysis, SQL Databases, Smartsheet, Microsoft Power Automate, Retrieval-Augmented Generation, System Availability, Prompt Engineering, Hallucination Detection, Generative AI, Agentic-AI, Data Analytics, Performance Monitor, Enterprise Integration, Virtual Agents, Azure AI, Automation Anywhere, Human in the Loop, Servicenow, Alteryx, Databricks
- **Published:** October 19, 2026
- **Apply:** https://iqvia.wd1.myworkdayjobs.com/IQVIA/job/Barcelona-Spain/Manager--Business-Systems-Analyst_R1562489

## About the Role

* 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., * 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.

## Description

* 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.