At a Glance
- Tasks: Build and maintain data pipelines using Python, SQL, and Spark in a collaborative team.
- Company: Join a global leader in information and analytics, making a real impact on science and healthcare.
- Benefits: Enjoy flexible working hours, generous vacation, and a comprehensive pension plan.
- Other info: Work in a dynamic environment with excellent growth opportunities and well-being initiatives.
- Why this job: Advance your career while contributing to innovative projects that benefit society.
- Qualifications: 2-3 years of experience in data or software engineering with a collaborative mindset.
The predicted salary is between 63000 - 77000 £ per year.
Are you passionate about building scalable, high-performance data-driven applications? Do you enjoy turning complex datasets into robust, reliable systems that deliver real business impact?
About the team: 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.
About the role: 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.
Key responsibilities:
- 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.
Requirements:
- 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.
Why join us? Join our team and contribute to a culture of innovation, collaboration, and excellence. If you are ready to advance your career and make a significant impact, we encourage you to apply.
Work in a way that works for you: 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 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.
We are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form.
Data Engineer II in London employer: LexisNexis Risk Solutions
At ICIS, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters collaboration and accountability. Our commitment to employee well-being is reflected in our generous benefits package, extensive learning opportunities, and a supportive environment that encourages personal and professional growth. Join us in our mission to optimize the world's resources while enjoying a fulfilling career in a globally distributed team that values your insights and contributions.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer II in London
✨Get Involved in Data Science Meetups
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We think you need these skills to ace Data Engineer II in London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at LexisNexis Risk Solutions, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at LexisNexis Risk Solutions. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at LexisNexis Risk Solutions
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at LexisNexis Risk Solutions!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
