Data Engineer reference: R100502

Senior Data Engineer Opportunity: Driving Innovation in Scientific Knowledge Discovery

This Senior Software Engineer II position at Elsevier offers a compelling opportunity for experienced data professionals to play a pivotal role in shaping the future of scientific discovery. You will join a dedicated team focused on transforming vast amounts of Elsevier's content into a powerful semantic data platform. This platform is designed to unlock critical insights for researchers, clinicians, and innovators worldwide, accelerating progress across research, healthcare, and life sciences.

The core mission of this role involves leading the design and implementation of complex, large-scale data pipelines and orchestration frameworks. You will be instrumental in evolving the data engineering architecture and building scalable, secure, and production-ready AI services, with a specific focus on reusable generative AI capabilities. If you are passionate about leveraging cutting-edge technology to drive meaningful impact and advance global knowledge-sharing, this role presents a significant career advancement opportunity.

Advantages for Potential Candidates:

• Impactful Mission: Contribute directly to advancing science and health by enabling researchers and healthcare professionals to gain new insights and make informed decisions.
• Cutting-Edge Technology: Work with advanced technologies such as Spark, Spark Streaming, Airflow, and generative AI, allowing you to stay at the forefront of data engineering innovation.
• Leadership and Mentorship: Take on a leadership role in system design and implementation, with opportunities to mentor junior team members and foster knowledge sharing.
• Career Growth: Engage in the design and development of evolving data engineering architecture, offering significant opportunities for professional development and skill enhancement.
• Collaborative Environment: Collaborate closely with product, platform, and other engineering teams to deliver high-quality, impactful solutions.
• Work-Life Balance & Benefits: Elsevier prioritizes employee well-being with flexible working hours, generous holiday allowances, comprehensive health and wellbeing programs, and various financial benefits.
• Global Reach: Be part of a global leader in information and analytics that tackles world-scale challenges and contributes to a more sustainable future.

Key Considerations for Career Path:

• Technical Depth: The role demands a strong foundation in distributed system design, data modeling, and performance optimization, particularly with tools like Spark and Airflow. Candidates with a proven track record in building and optimizing large-scale batch and streaming data systems will thrive.
• Software Engineering Excellence: A commitment to writing clean, modular, and testable code, along with experience in test-driven development and CI/CD practices, is crucial.
• Problem-Solving Acumen: The ability to independently drive technical outcomes from problem identification to deployment, and to troubleshoot complex distributed data systems, is a key requirement.
• Agile Methodology: Familiarity with Agile or other iterative development methodologies will be beneficial for seamless integration into the team's workflow.
• Graph Technology Exposure (Nice to Have): While not strictly required, prior experience with graph-based data models or knowledge graph architecture would be a significant advantage, aligning with the team's focus on interconnected knowledge.
• Platform Building Experience (Nice to Have): Experience in building internal platforms or reusable engineering components can contribute to the team's efficiency and scalability.
• Observability Best Practices (Nice to Have): Knowledge of best practices for observability in data systems, such as logging, metrics, and alerting, will be a valuable asset.

This is an exceptional opportunity for a Senior Data Engineer looking to make a substantial impact in a dynamic and forward-thinking organization. By joining Elsevier, you will be at the forefront of knowledge discovery, contributing to advancements that benefit society on a global scale.