At a Glance
- Tasks: Build and maintain data pipelines using Python, SQL, and Spark in a collaborative team.
- Company: Join Elsevier, a global leader in information and analytics for science and healthcare.
- Benefits: Enjoy flexible hours, generous vacation, and a comprehensive pension plan.
- Other info: Collaborative environment with opportunities for professional growth and learning.
- Why this job: Make a real impact on research and healthcare while growing your skills with AI technologies.
- Qualifications: 2-3 years of experience in data or software engineering; proficiency in Python and SQL.
The predicted salary is between 35000 - 45000 £ per year.
Overview
The Search and AI Platform supports core products such as Scopus, Science Direct, 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.
Responsibilities
- Build and maintain data pipelines and services under the guidance of senior engineers.
- Work with technologies such as Python, SQL, Spark, and Airflow to process large-scale data.
- Use AI-assisted development tools such as Claude Code, Copilot, or Codex as part of your workflow.
- Contribute to ELT and ETL pipelines for data ingestion into search, graph, and relational data stores.
- Write clean, well-tested code and apply software engineering best practices, including CI/CD.
- Contribute to cloud infrastructure on AWS with support from the wider team.
- Participate in code reviews and actively seek feedback to accelerate growth.
- Collaborate with product, platform, and data science teams to deliver business value.
Qualifications
- 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.
- 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; experience with search, graph, or large-scale analytical databases; interest in AI, machine learning pipelines, or embedding generation.
Benefits
- We promote a healthy work/life balance across the organization.
- Flexible working hours to help you fit everything in and work when you are most productive.
- Comprehensive Pension Plan, generous vacation entitlement, sabbatical leave options, and family leave.
- Internal communities and networks, various employee discounts, and an Employee Assistance Program (global).
- About the business
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.
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.
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