Are you excited to design and operate large‑scale data platforms that power global research and innovation?
Do you enjoy collaborating across teams to build reliable, compliant, cloud‑based data solutions?
About our Team
Elsevier is a global information analytics company that helps institutions and professionals progress science, advance healthcare and improve performance for the benefit of humanity. We serve the research, academic, and clinical communities through the application of technology and analytics to content. Our portfolio of solutions brings together extensive Scientific, Technical and Medical content, powerful analytics, and technologies. We help our corporate customers, R&D professionals, engineers, scientists, and commercial marketing leaders, to innovate and commercialize ideas, products, and processes.
About the Role
This role is responsible for designing, delivering and operating China‑local content management and data processing systems. You will work close to code, data pipelines, and production systems, solving real implementation problems related to scale, data quality, operability, and compliance in the China environment. The position works from designs and requirements provided by Product Solution Architect and Product teams, collaborate closely with business stakeholders and engineering teams to translate requirements into technical solutions. A key objective is to ensure high standards of data quality, performance, and governance. You will support integration across enterprise systems and third-party platforms. Overall, you will play a critical role in enabling data-driven transformation from global products’ offering to integrate with local solutions and serve China customers’ needs.
Responsibilities
- Design, implement, test, and maintain production‑grade backend services and data pipelines in cloud environment
- Write clean, maintainable, and efficient code for large‑scale content ingestion, processing, and delivery
- Debug and resolve complex issues including data correctness, performance bottlenecks, and operational failures
- Participate in code reviews and contribute to shared libraries, reusable components, and internal tooling
- Build and operate pipelines processing high‑volume scholarly content, including XML and other semi‑structured formats
- Implement metadata extraction, transformation, validation, deduplication, and enrichment logic
- Handle imperfect inputs such as non‑standard schemas, missing fields, inconsistent source data, with encoding issues
- Implement ETL/ELT processes for structured and unstructured data
- Integrate internal systems with third-party platforms via APIs and middleware
- Implement data quality checks, automated testing, and observability to ensure data quality, consistency, and performance
- Optimize data pipelines and system performance across systems
- Implement automated workflows for content processing, validation, and policy enforcement
- Reduce manual operational steps through engineering automation
- Ensure compliance with China regulatory requirements, including Cybersecurity Law and PIPL
- Support audits through technical controls such as logging, lineage tracking, and access trails
- Collaborate with cross-functional teams and stakeholders
- Support system migrations, upgrades, and cloud adoption
- Monitor and troubleshoot data and integration issues
- Maintain documentation for data architecture and workflows
- Investigate incidents, perform root‑cause analysis, and implement permanent fixes
Requirements
- 5+ years of hands‑on experience as a software engineer on backend or data‑intensive systems
- Bachelor's degree or above in Computer Science, Software Engineering, or a related field.
- Strong understanding of software engineering fundamentals: data structures, system design basics, testing, and debugging
- Advanced relational database expertise and data warehouse project experience
Mandatory Skills
- Strong programming experience in Python or Java
- Advanced SQL and relational database expertise
- Hands-on experience with Snowflake for data warehousing
- Hands-on experience with ETL/ELT pipelines
- Experience with cloud platforms (AWS, or Alibaba Cloud)
- Hands-on experience with Databricks, Spark and Kafka for data processing
- Experience with NoSQL databases (MongoDB, Cassandra, etc.)
- Strong API and integration knowledge (REST, SOAP, JSON, XML)
- Experience with system integration and data exchange mechanisms
- Familiarity with data visualization tools (Tableau, Power BI)
- Knowledge of DevOps practices and CI/CD pipelines
- Experience with containerization (Docker, Kubernetes)
- Experience of projects execution following data governance and compliance standards
- Solid understanding of data lifecycle management and architecture
- Experience in performance tuning and troubleshooting
- Experience in data pipeline monitoring and reliability engineering
- Strong understanding of security principles in data systems
- Reading/Writing proficiency in English for technical reviews
- Experience of oral English communication with global teams for meetings and reviews
Soft Skills
- Strong problem-solving and analytical thinking
- Excellent communication and stakeholder management skills
- Ability to translate business needs into technical solutions
- Strong collaboration in cross-functional teams
- Ability to work independently and manage priorities
- High attention to detail and quality focus
- Experience working in global or distributed teams
- Strong ownership and accountability mindset
- Continuous learning and adaptability to new technologies
- Customer-oriented and results-driven mindset
Optional Skills
- Experience with machine learning tools (TensorFlow, SageMaker)
- Knowledge of search platforms (Elasticsearch, ELK)
- Experience with data modeling and pipeline automation
- Exposure to enterprise analytics or digital transformation projects
- Familiarity with AI-assisted development tools
- Understanding of data medallion (Bronze / Silver / Gold) architecture
- Knowledge of data compliance standards (GDPR, HIPAA) and data security best practices
- Experience of analytical solutions using cloud-native, big data and NoSQL technologies
- Experience with enterprise systems such as ERP, CRM
- Experience with MCP, AI Agents development
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.
Working for You
We know that your wellbeing and happiness are key to a long and successful career. These are some of the benefits we are delighted to offer:
- Medical and Life Insurance
- Long‑Service Award
- Marriage and New Baby Gifts
- Festivals and Birthday Gifts
- Annual Medical Check‑up
- Flexible Benefits via CIIC Platform
- Paid Time Off, including annual leave, family care leave, and public holidays
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.







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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