Associate Director, Data Engineer

October 16, 2026

Hybrid

Lead

Barcelona

Indeed

Keep in mind

Work authorization required

Also worth knowing

Mandatory office attendance

Description

Senior data engineering role in the R&D Data Office focused on reusable, enterprise-grade data capabilities. The hire turns scientific and business requirements into modular, configurable solutions for workflows such as SafetyOmics and AI4Assay, applying FAIR+T principles and AI-assisted development. The position includes technical leadership, mentoring and delivery coordination within a small agile team.

Responsibilities

Prototype, design, develop, and deploy modular configurable data solutions for complex end-to-end R&D workflows
Translate scientific and business requirements into clear designs and implementation plans
Move solutions from prototype to production with operational readiness, lifecycle management, and continuous improvement
Work within architecture, security requirements, and operational constraints, making pragmatic recommendations when options or limitations arise
Apply modern engineering practices including version control, automated testing, CI/CD, monitoring, observability, and documentation
Evaluate technical options and advise on trade-offs across scalability, maintainability, security, cost, performance, and reuse
Plan and track delivery, manage risks and dependencies, and provide timely transparent updates
Collaborate with solution architects, data engineers, semantic modellers, and other specialists to deliver robust products
Mentor junior colleagues and contribute to a culture of technical learning and continuous improvement
Coordinate delivery across internal contributors and outsourced partners
Troubleshoot issues affecting performance, data flows, metadata integrity, and production reliability
Engineer solutions that implement FAIR+T principles with end-to-end traceability, discoverability, and trustworthy use
Engage on data quality, metadata, and governance, resolving issues with the right partners
Identify where AI-assisted development, automation, and agent-based approaches can improve productivity and data-management workflows
Map critical workflows and deliver a high-value prototype for initiatives such as SafetyOmics or AI4Assay
Standardize and scale reusable capabilities that reduce assay cycle time and improve data traceability
Help shape enterprise data standards and platforms that enable automation across pre-clinical research

Requirements

Demonstrated experience designing, developing, deploying, and maintaining data and software solutions for complex business, scientific, or operational workflows
Strong programming experience in Python and working knowledge of other relevant programming languages
Practical experience developing and deploying solutions using AWS or other cloud services such as Amazon S3, AWS Lambda, AWS Step Functions, Amazon CloudWatch, AWS IAM
Experience working with relational databases and data integration or processing workflows
Ability to design modular, configurable, maintainable, and reusable solutions
Ability to translate business or scientific needs into technical requirements and pragmatic solution approaches
Experience planning and delivering technical work in an agile environment, including tracking progress, managing risks and dependencies, reporting to stakeholders
Ability to evaluate technical options and clearly explain trade-offs on scalability, maintainability, security, cost, performance, and reuse
Understanding of, or strong interest in, data quality, metadata, and FAIR principles with troubleshooting of data and metadata issues
Interest in using AI capabilities, AI-assisted development, automation, and agent-based solutions to improve engineering productivity
Experience with non-relational databases such as graph, document, key-value, or analytical databases
Experience with data integration, metadata management, semantic web technologies (RDF, OWL, SHACL, SPARQL), data governance, or FAIR data practices
Interest in, or experience of, pharmaceutical R&D, particularly pre-clinical research, laboratory workflows, or scientific data
Experience working in regulated, privacy-sensitive, or otherwise controlled environments
Experience mentoring colleagues or coordinating technical delivery through influence
Experience applying AI agents or automation to scientific, data-management, or software-development workflows

Conditions

Full-time contract with retirement plan and long service award
Health and travel insurance alongside annual leave and reduced-hours timetables
Inclusive workplace with no salary gap and fully accessible positions
Recognised as an award-winning employer with strong employee recommendation rates
In-office role in Barcelona with a minimum of three days per week on-site and no remote flexibility