Agentic AI, Data Engineer COA Accelerator

IQVIA LLC; Madrid; Presencial; EUR 55.000 - 80.000; Jornada completa

Descripción de la vacante

IQVIA’s COA team is seeking a Data Engineer to transform fragmented clinical, regulatory, and scientific content into structured, AI-ready knowledge assets powering AI-enabled COA workflows. You will design robust ingestion pipelines, governance, and metadata enrichment to support evidence retrieval and expert review across global clients.

Join a collaborative, multi-disciplinary team and contribute to scalable data solutions that underpin COA research and strategy.

Formación

• Degree in a technical field (computer science, data engineering, etc.).
• Experience designing and maintaining data pipelines for structured and unstructured data.
• Strong Python and SQL skills.
• Experience with APIs, relational databases, document stores, search indexes, cloud data platforms, and ETL/ELT workflows.
• Experience handling large volumes of text-heavy documents (PDFs, reports, literature).
• Strong understanding of data cleaning, normalisation, metadata management, document parsing, indexing, lineage, versioning, and auditability.
• Familiarity with data modelling for scientific, clinical, regulatory, or healthcare content.
• Ability to translate domain requirements into practical data structures and retrieval-ready content.
• Strong attention to data quality and source traceability.
• Ability to collaborate with AI engineers, product managers, scientists, software engineers, and legal/commercial teams.
• Experience with life sciences data preferred.
• Fluency in English.

Responsabilidades

• Design, build, and maintain data infrastructure that supports IQVIA’s AI-enabled COA strategy and COA Accelerator capabilities.
• Own ingestion, transformation, normalisation, enrichment, indexing, versioning, and governance of data sources.
• Build ingestion pipelines for structured and unstructured sources including PDFs, documents, databases, APIs, and publications.
• Transform raw material into standardised, searchable, AI-ready formats supporting retrieval and citation workflows.
• Develop repeatable processes for parsing, OCR, metadata enrichment, chunking, deduplication, versioning, indexing, and quality control.
• Provide technical support to teams building the platform’s knowledge layer, including instrument metadata and regulatory evidence.
• Support integration of public data sources such as clinical trial registries, FDA/EMA data, HTA, literature.
• Support ingestion of proprietary internal knowledge and publications.
• Prepare data for retrieval-augmented generation with robust chunking and indexing.
• Collaborate with AI engineers to improve precision, recall, and citation accuracy.
• Maintain audit trails and data quality controls across ingestion and transformations.
• Ensure data-use aligns with governance, licensing, and privacy requirements.
• Collaborate across AI Engineering, Product, COA Science and Software Engineering.

Conocimientos

Python

SQL

APIs

ETL/ELT

OCR

Text processing

Data cleaning

Metadata management

Indexing

Versioning

Governance

Documentation

Collaboration

English fluency

Educación

Degree in computer science, data engineering, data science, information systems, bioinformatics, computational biology, engineering, or related field

Herramientas

Elasticsearch/OpenSearch

Azure AI Search

Pinecone

Weaviate

Milvus

Qdrant

Cloud data platforms (Azure/AWS/GCP)

Descripción del empleo

Job Description Summary

IQVIA provides scientific services spanning clinical trials, real world evidence, and consulting in all areas of the product lifecycle. Our Clinical Outcomes Assessments (COAs) organisation leads the industry in generating data to ensure that the patient voice is incorporated into the development and commercialisation of medication and other drug/non-drug interventions. We focus on understanding and meeting the needs of our clients – mostly life science/pharmaceutical companies – through the application of broad consulting expertise and technical scientific knowledge to conduct scientifically rigorous research. This research is broad and includes qualitative, quantitative, and passive approaches to understand patient, caregiver, and healthcare professional experiences and expectations of disease and treatment. The COA Accelerator ecosystem is expanding its AI-enabled capabilities to help internal teams and external clients generate evidence-backed COA strategy recommendations. These capabilities depend on high-quality, traceable, well-governed, AI-ready data assets spanning COA instrument information, psychometric evidence, regulatory precedent, clinical trial records, scientific publications, internal consulting deliverables, and related sources. The Data Engineer will play a critical role in transforming fragmented clinical, regulatory, scientific, and proprietary content into structured, searchable, and secure knowledge assets that power AI-enabled COA strategy workflows. To meet our client expectations and retain the excellent reputation built up over time, the IQVIA COAs team is committed to recruiting, training and supporting driven individuals who have life science, consulting, product development, data engineering, and/or AI-enabledment skills that can be applied to COA research and technology-enabled offerings. Individuals joining us are assured of a rewarding and progressive career in patient-focused research. You’ll have the opportunity to address challenging client issues, across multiple geographies, with a hands-on influence in developing and delivering innovative solutions. We operate in a truly multi-cultural, collegial and collaborative work environment that is rich in development and growth.

Role & Responsibilities

• Design, build, and maintain data infrastructure that supports IQVIA’s AI-enabled COA strategy and COA Accelerator capabilities.
• Own the ingestion, transformation, normalisation, enrichment, indexing, versioning, and governance of public, proprietary, and client-specific data sources.
• Build ingestion pipelines for structured and unstructured sources, including PDFs, Word documents, slide decks, spreadsheets, databases, APIs, clinical trial registries, regulatory documents, scientific publications, and internal repositories.
• Transform raw source material into standardised, searchable, AI-ready formats that support evidence retrieval, source citation, recommendation generation, and expert review workflows.
• Develop repeatable processes for document parsing, OCR, text extraction, metadata enrichment, chunking, deduplication, versioning, indexing, and quality control.
• Provide technical support to the teams building and maintaining the platform’s core knowledge layer, including COA instrument metadata, instrument versions, translations, modes of administration, usage rights, psychometric evidence, therapeutic area mappings, endpoint usage, regulatory precedent, and related scientific evidence.
• Support integration of public data sources such as clinical trial registries, FDA labels, EMA EPARs, HTA records, scientific literature, FDA guidance, public qualification documents, and other relevant evidence repositories.
• Support ingestion of proprietary internal knowledge, publications, thought leadership, other expert-authored content.
• Prepare data for retrieval-augmented generation workflows through high-quality chunking, embeddings, indexes, metadata filters, and source reference structures.
• Collaborate with AI engineers to improve retrieval precision, recall, relevance, and citation accuracy.
• Implement hybrid retrieval approaches combining semantic search, keyword search, structured database queries, and metadata filtering.
• Maintain traceability between AI-generated outputs and source documents.
• Implement data quality controls to identify incomplete, outdated, duplicated, poorly parsed, incorrectly tagged, or otherwise unreliable content.
• Maintain audit trails for source ingestion, transformation, updates, deletions, access rights, and downstream use.
• Work with legal, security, compliance, product, and domain stakeholders to ensure data use aligns with contractual, licensing, privacy, intellectual property, and governance requirements.
• Collaborate across AI Engineering, Product, COA Science and Software Engineering.

Skills & Qualifications

• Degree in computer science, data engineering, data science, information systems, bioinformatics, computational biology, engineering, or a related technical field.
• Experience designing, building, and maintaining data pipelines for structured and unstructured data.
• Strong Python and SQL skills.
• Experience with APIs, relational databases, document stores, search indexes, cloud data platforms, and ETL/ELT workflows.
• Experience handling large volumes of text-heavy documents such as PDFs, slide decks, reports, publications, regulatory files, scientific literature, or knowledge repositories.
• Strong understanding of data cleaning, normalisation, metadata management, document parsing, indexing, lineage, versioning, and auditability.
• Familiarity with data modelling approaches for complex knowledge domains, including scientific, clinical, regulatory, or healthcare content.
• Ability to translate domain expert requirements into practical data structures, metadata models, retrieval-ready content, and maintainable pipelines.
• Strong attention to detail and ability to identify data quality issues that could affect AI outputs, source traceability, or regulatory credibility.
• Ability to collaborate effectively with AI engineers, product managers, COA scientists, software engineers, security stakeholders, legal teams, and commercial teams.
• Strong documentation skills, including ability to document data sources, transformations, lineage, access rules, data quality checks, and known limitations.
• Experience in life sciences, clinical research, healthcare, regulatory data, scientific publishing, HEOR, clinical outcome assessments, patient-reported outcomes, or medical evidence management is strongly preferred.
• Experience with clinical trial registries, regulatory labels, HTA reports, scientific literature databases, medical knowledge repositories, or similar evidence sources.
• Experience with vector databases, embeddings, semantic search, Elasticsearch/OpenSearch, Azure AI Search, Pinecone, Weaviate, Milvus, Qdrant, or similar technologies.
• Experience with cloud data platforms such as Azure, AWS, or GCP.
• Experience with document AI, OCR, layout-aware parsing, table extraction, metadata enrichment, taxonomy development, or controlled vocabularies is desirable.
• Familiarity with ontology development, biomedical terminologies, controlled vocabularies, evidence classification, and structured knowledge representation.
• Understanding of GDPR, data privacy, intellectual property constraints, licensed content, confidential client data, access control, and secure data handling.
• Ability to work independently in a remote or hybrid environment while collaborating across global teams.
• Significant experience leveraging AI tools for work.
• Fluency in English.

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. IQVIA is a leading global provider of clinical research services, commercial insights and healthcare intelligence to the life sciences and healthcare industries. We create connections that accelerate the development and commercialization of innovative medical treatments. Everything we do is part of a journey to improve patient outcomes and population health worldwide. To get there, we seek out diverse talent with curious minds and a relentless commitment to innovation and impact. No matter your role, everyone at IQVIA contributes to our shared goal of helping customers improve the lives of patients everywhere. Thank you for your interest in growing your career with us.