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- Tasks: Design and build complex data systems for analytics and AI capabilities.
- Company: LexisNexis Intellectual Property, a leader in data solutions.
- Benefits: Health screening, private medical benefits, study assistance, and sabbaticals.
- Why this job: Shape the future of data engineering and work on innovative AI projects.
- Qualifications: Strong SQL Server experience and knowledge of cloud-based Data Lakes.
- Other info: Promotes work/life balance with numerous wellbeing initiatives.
The predicted salary is between 36000 - 60000 £ per year.
As a Senior Data Engineer at LexisNexis Intellectual Property (LNIP), you will play a key technical leadership role in designing, building, and evolving complex data systems that support both traditional analytics and emerging AI capabilities. You will help shape the architecture and standards that underpin mission-critical products, including data pipelines that enable machine learning, LLM-powered features, and AI experimentation at scale. This role is critical in ensuring the integrity, security, observability, scalability, and long-term sustainability of business-critical data platforms.
Responsibilities:
- Mentor, coach and support other data engineers, contributing to knowledge sharing, technical growth, and engineering excellence.
Requirements:
- Strong experience with SQL Server and cloud-based Data Lakes (Azure and/or AWS).
- Deep knowledge of large-scale data platforms such as Databricks and Snowflake.
- Familiarity with cloud-native tools including Azure Synapse and Redshift.
- Experience building data pipelines that support AI/ML workloads.
- Hands-on experience with Spark.
- Experience working with test-driven development (TDD) approaches.
- Having experience with LLM or GenAI initiatives—such as preparing data for embeddings, working with vector databases, or implementing retrieval-augmented generation (RAG)—would be a bonus.
- It would also be advantageous to have familiarity with technologies like Elasticsearch, Solr, PostgreSQL, Databricks, Delta Lake, and Delta Share.
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.
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:
- Health screening, eye care vouchers and private medical benefits
- Optional Dental Insurance
We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits.
Senior Data Engineer II employer: LexisNexis Risk Solutions
Contact Detail:
LexisNexis Risk Solutions Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Engineer II
✨Tip Number 1
Network like a pro! Reach out to current employees at LexisNexis or in the data engineering field. A friendly chat can give you insider info and maybe even a referral, which can really boost your chances.
✨Tip Number 2
Show off your skills! Prepare a portfolio showcasing your projects, especially those involving SQL Server, cloud-based Data Lakes, and AI/ML workloads. This will help you stand out during interviews and demonstrate your hands-on experience.
✨Tip Number 3
Practice makes perfect! Get comfortable with common interview questions for data engineers, especially around data pipelines and TDD approaches. Mock interviews with friends or mentors can help you nail your responses.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining the team at LexisNexis.
We think you need these skills to ace Senior Data Engineer II
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the Senior Data Engineer role. Highlight your experience with SQL Server, cloud-based Data Lakes, and any relevant projects you've worked on that showcase your data engineering prowess.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about data engineering and how your background aligns with our mission at StudySmarter. Don’t forget to mention any experience with AI/ML workloads or relevant technologies.
Showcase Your Technical Skills: In your application, be sure to include specific examples of your technical skills, especially with tools like Databricks, Snowflake, and Spark. We want to see how you’ve used these in real-world scenarios to solve problems or improve processes.
Apply Through Our Website: We encourage you to apply directly through our website for the best chance of getting noticed. It’s the easiest way for us to keep track of your application and ensure it reaches the right people!
How to prepare for a job interview at LexisNexis Risk Solutions
✨Know Your Data Inside Out
Make sure you brush up on your SQL Server and cloud-based Data Lakes knowledge, especially Azure and AWS. Be ready to discuss your experience with large-scale data platforms like Databricks and Snowflake, as well as any hands-on projects you've worked on that involved building data pipelines for AI/ML workloads.
✨Show Off Your Mentoring Skills
Since this role involves mentoring other data engineers, think of examples where you've coached or supported colleagues in the past. Prepare to share how you contributed to their technical growth and how you fostered a culture of knowledge sharing within your team.
✨Get Familiar with TDD
Test-driven development (TDD) is key in this role, so be prepared to discuss your experience with it. Bring examples of how you've implemented TDD in your previous projects and how it has improved the quality of your code and the overall project outcomes.
✨Highlight Your AI/ML Experience
If you've worked with LLM or GenAI initiatives, make sure to highlight that experience. Discuss any specific projects where you prepared data for embeddings or worked with vector databases. This will show your potential employer that you're not just technically skilled but also aligned with their focus on emerging AI capabilities.
