Are you passionate about leading large-scale engineering organisations and shaping the future of research analytics through data, AI and modern platform engineering?
Do you enjoy developing engineering leaders, driving technical strategy, and delivering innovative solutions that help researchers make better decisions?
About our Team
SciVal is Elsevier’s research-analytics platform. It helps universities, research institutions and funding organizations evaluate research performance, benchmark against peers, understand collaboration networks, identify emerging research areas, and support evidence-based strategic decisions. SciVal is built on trusted, connected research data, including Scopus. Learn more about SciVal.
About the Role
As an Engineering Director supporting SciVal, you will lead multiple engineering teams responsible for delivering a scalable, secure, and data-intensive analytics platform. You will partner closely with Product, Data, Architecture, Quality Engineering, Security, UX and commercial stakeholders to shape technical strategy, modernise platform capabilities, and enable AI-assisted and agent-ready experiences for customers.
You will play a key leadership role in driving engineering excellence, developing technical talent, and ensuring the successful delivery of technology roadmaps that support research analytics and discovery solutions.
Responsibilities
Lead SciVal’s engineering strategy and technical direction in partnership with Product, Data and Architecture.
Define and uphold architectural standards across search, data, analytics, APIs and platform integration, aligned with Elsevier governance.
Balance engineering excellence, innovation, cost efficiency and pragmatic delivery across the platform.
Lead distributed engineering teams across frontend, backend, data and quality engineering.
Hire, coach and develop high-performing engineers, engineering managers and technical leaders.
Own workforce planning, succession planning, performance management and resource allocation.
Drive planning, prioritisation and execution across multiple engineering teams and programmes.
Maintain strong engineering standards for code quality, testing, release management, observability, security and operational resilience.
Establish clear operating models for technical debt, production incidents, operational risk and partner delivery.
Lead platform modernisation, consolidation and adoption of shared technology foundations to improve scalability, reliability and cloud-cost efficiency.
Partner with Product, UX, Data and customers to improve Research Analytics workflows and enable AI-assisted, agent-ready experiences.
Communicate technical trade-offs, dependencies, risks and delivery progress clearly to senior stakeholders and roadmap forums.
Requirements
Experience in software engineering, including significant experience leading engineering managers, engineering leads and distributed teams across multiple geographies and time zones.
Proven experience delivering large-scale, data-intensive software products in production.
Demonstrated success setting technical strategy and delivering technology roadmaps.
Demonstrated experience introducing AI-assisted development practices across engineering teams.
Excellent communication, planning, influencing and stakeholder-management skills.
Experience with large-scale data ingestion, transformation, indexing and query optimisation.
Understanding of search, discovery and graph-based data relationships, particularly within research and scholarly domains.
Familiarity with analytics-driven systems, knowledge graphs or metadata-rich datasets.
Experience delivering AI-enabled product capabilities such as summarization, guided workflows, intelligent search or decision support.
Understanding of making data platforms accessible to AI agents through APIs, metadata, data contracts or MCP-compatible interfaces.
Experience with AI adoption in SDLC streams.
Work in a Way That Works for You
We promote a healthy work/life balance across the organisation. We offer an appealing working prospect for our people. With numerous wellbeing initiatives, shared parental leave, study assistance, and sabbaticals, we will help you meet your immediate responsibilities and your long-term goals.
Working Pattern
Working flexible hours - flexing the times when you work in the day to help you fit everything in and work when you are the most productive.
About the Business
A global leader in information and analytics, we help researchers and healthcare professionals advance science and improve health outcomes for the benefit of society. Building on our publishing heritage, we combine quality information and vast data sets with analytics to support visionary science and research, health education and interactive learning, as well as exceptional healthcare and clinical practice. At Elsevier, your work contributes to the world's grand challenges and a more sustainable future. We harness innovative technologies to support science and healthcare to partner for a better world.
If performed in NLD Amsterdam (Radarweg), the base pay range is €110,500 - €184,000.We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location.
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Skills Required
- Experience in software engineering with significant experience leading engineering managers, engineering leads, and distributed teams across multiple geographies and time zones.
- Proven experience delivering large-scale, data-intensive software products in production.
- Demonstrated success setting technical strategy and delivering technology roadmaps.
- Demonstrated experience introducing AI-assisted development practices across engineering teams.
- Excellent communication, planning, influencing, and stakeholder-management skills.
- Experience with large-scale data ingestion, transformation, indexing, and query optimization.
- Understanding of search, discovery, and graph-based data relationships, particularly within research and scholarly domains.
- Familiarity with analytics-driven systems, knowledge graphs, or metadata-rich datasets.
- Experience delivering AI-enabled product capabilities such as summarization, guided workflows, intelligent search, or decision support.
- Understanding of making data platforms accessible to AI agents through APIs, metadata, data contracts, or MCP-compatible interfaces.
- Experience with AI adoption in software development lifecycle streams.
Elsevier Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Elsevier and has not been reviewed or approved by Elsevier.
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Leave & Time Off Breadth — Feedback suggests paid time off spans vacation, holidays, sick days, bereavement, military leave, and volunteer time. Family-related leave options are also emphasized as part of the package.
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Healthcare Strength — Feedback suggests medical, dental, vision, life insurance, wellness initiatives, and an EAP form a comprehensive health offering. Gym support and wellbeing hubs reinforce an ongoing health and wellness focus.
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Retirement Support — Feedback suggests retirement programs include a 401(k)/retirement plan and pension options, with long-term savings vehicles such as an employee stock purchase plan also available. These elements contribute to a sense of financial security beyond base pay.
Elsevier Insights
What We Do
Elsevier is a world-leading provider of information solutions that enhance the performance of science, health, and technology professionals, empowering them to make better decisions, and deliver better care. Because informed decisions lead to better outcomes, Elsevier is a leader in information and analytics for customers across the global research and health ecosystems. Elsevier helps researchers and healthcare professionals advance science and improve health outcomes for the benefit of society. We do this by facilitating insights and critical decision-making for customers across the global research and health ecosystems.
