Data Engineer II

The Search and AI Platform supports core products such as Scopus, ScienceDirect, and AI-driven research solutions. As a Junior Data Engineer, you will work hands-on building and maintaining data pipelines and services, growing your skills alongside experienced engineers in a collaborative team environment.,

• Building and maintaining data pipelines and services under the guidance of senior engineers.
• Working with technologies such as Python, SQL, Spark, and Airflow to process large-scale data.
• Using AI-assisted development tools such as Claude Code, Copilot, or Codex as part of your workflow.
• Contributing to ELT and ETL pipelines for data ingestion into search, graph, and relational data stores.
• Writing clean, well-tested code and learning best-practice software engineering principles, including CI/CD.
• Contributing to cloud infrastructure on AWS, with support from the wider team.
• Participating in code reviews and actively seeking feedback to accelerate your growth.
• Collaborating with product, platform, and data science teams to deliver business value.
  
  This position is suited for an early-career professional with 2-3 years of experience who will contribute to research, design, and software development assignments within a software functional area or product line. Working under the guidance of senior team members, this position supports project delivery by participating in planning discussions and following established methodologies. The role involves contributing to software design at the component level, learning and applying best practices through hands-on work and code reviews, and developing communication skills by engaging with team members to understand requirements and translate them into solutions., 2-3 years of commercial experience as a data or software engineer, including some exposure to production systems.
• Proficiency in Python, SQL, and Spark.
• Basic understanding of data engineering concepts including batch processing and relational databases.
• Some hands-on experience with data pipeline tools; exposure to Spark or Airflow is a plus.
• Familiarity with cloud platforms (preferably AWS); production experience is not required.
• A collaborative mindset and willingness to learn and communicate openly within the team.
Nice to have
• Exposure to data lake concepts or formats such as Delta Lake or Iceberg.
• Any experience with search, graph, or large-scale analytical databases.
• Interest in AI, machine learning pipelines, or embedding generation.
  
  We promote a healthy work/life balance across the organization. We offer an appealing working prospect for our people. With numerous wellbeing initiatives and shared parental leave, we will help you meet your immediate responsibilities and your long-term goals.
• 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 well-being and happiness are key to a long and successful career. These are some of the benefits we are delighted to offer:
• Comprehensive Pension Plan
• Generous vacation entitlement and option for sabbatical leave
• Maternity, Paternity, Adoption, and Family Care Leave
• Flexible working hours
• Personal Choice budget
• Internal communities and networks
• Various employee discounts
• Recruitment introduction reward
• Employee Assistance Program (global)
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.