Data Engineer II

Data Engineer II

Full-Time 36000 - 60000 ÂŁ / year (est.) No home office possible
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At a Glance

  • Tasks: Design and maintain data systems for analytics and AI/ML capabilities.
  • Company: Join LexisNexis, a leader in legal and business information.
  • Benefits: Generous holiday allowance, health benefits, and extensive learning resources.
  • Why this job: Make a real impact on innovation and help advance humanity.
  • Qualifications: Experience with SQL Server, cloud Data Lakes, and modern Data Engineering.
  • Other info: Promotes work/life balance with wellbeing initiatives and volunteer opportunities.

The predicted salary is between 36000 - 60000 ÂŁ per year.

About Our Team

At LexisNexis Intellectual Property Solutions, our mission is to bring clarity to innovation by delivering better outcomes to the innovation community. Each day, the work our team does supports the development of new technologies and processes that ultimately advance humanity. Helping our customers reach their goals is our primary focus. We enable innovators to accomplish more by helping them make informed decisions, be more productive, comply with regulations and ultimately achieve superior results. Our overall success is measured by how well we deliver these results. We are proud to directly support and serve these innovators in their endeavors to better humankind.

About The Role

As a Data Engineer at LexisNexis Intellectual Property (LNIP), you will design, build, and maintain complex data systems that support both traditional analytics and emerging AI/ML-driven capabilities. You’ll contribute to the evolution of a modern Data Platform that underpins mission‑critical products, including data pipelines that enable machine learning, LLM‑powered features, and AI experimentation at scale. Your role will be critical in ensuring the integrity, security, observability, and accessibility of business‑critical data.

Responsibilities

  • Be a hands‑on Data Engineer working across our ecosystem of products and Data Platforms.
  • Interface with data scientists, AI engineers, and other technical stakeholders to finalize requirements and enable production‑ready AI use cases.
  • Develop and maintain data infrastructure supporting real‑time and batch data processing in streaming and event‑driven architectures.
  • Build and operate scalable data ingestion, feature engineering, and ML/LLM data pipelines, incorporating Data Lakehouse concepts for unified data management.
  • Support MLOps workflows, including dataset versioning, experiment tracking inputs, model training data pipelines, and inference data flows.
  • Successfully implement development processes, coding best practices, automated testing, and code reviews.
  • Design and maintain APIs and data services that support analytics, ML, and downstream AI applications, ensuring strong data lineage and observability.
  • Apply DataOps principles to improve system reliability, performance, monitoring, and deployment automation.
  • Automate system lifecycle management and infrastructure where appropriate to ensure robustness, scalability, and cost efficiency.
  • Collaborate on the integration of LLMs and AI services (e.g., embedding pipelines, vectorized data preparation, prompt‑related data flows).
  • Resolve technical issues as necessary and contribute to root cause analysis.

Requirements

  • Strong experience with SQL Server and cloud‑based Data Lakes (Azure and/or AWS).
  • Proven background in modern Data Engineering, including building production‑grade pipelines.
  • 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.
  • Understanding of Scrum, Kanban, and Agile software development methodologies.
  • Hands‑on experience with Spark.
  • It would also be advantageous to have familiarity with technologies like Elasticsearch, Solr, PostgreSQL, Databricks, Delta Lake, and Delta Share.

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 For You

  • Generous holiday allowance with the option to buy additional days.
  • Health screening, eye care vouchers and private medical benefits.
  • Wellbeing programs.
  • Life assurance.
  • Access to a competitive contributory pension scheme.
  • Save As You Earn share option scheme.
  • Travel Season ticket loan.
  • Electric Vehicle Scheme.
  • Optional Dental Insurance.
  • Maternity, paternity and shared parental leave.
  • Employee Assistance Programme.
  • Access to emergency care for both the elderly and children.
  • RECARES days, giving you time to support the charities and causes that matter to you.
  • Access to employee resource groups with dedicated time to volunteer.
  • Access to extensive learning and development resources.
  • Access to employee discounts scheme via Perks at Work.

About The Business

LexisNexis Legal & Professional® provides legal, regulatory, and business information and analytics that help customers increase their productivity, improve decision‑making, achieve better outcomes, and advance the rule of law around the world. As a digital pioneer, the company was the first to bring legal and business information online with its Lexis® and Nexis® services. We know your well‑being and happiness are key to a long and successful career. We are delighted to offer country specific benefits.

Data Engineer II employer: LexisNexis

At LexisNexis Intellectual Property Solutions, we pride ourselves on being an exceptional employer that champions innovation and employee well-being. Our collaborative work culture fosters growth through extensive learning opportunities and a commitment to work-life balance, complemented by generous benefits such as health screening, flexible leave options, and a competitive pension scheme. Join us in our mission to support the innovation community while enjoying a fulfilling career in a supportive environment.
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Contact Detail:

LexisNexis Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Data Engineer II

✨Tip Number 1

Network like a pro! Reach out to current employees at LexisNexis on LinkedIn or through mutual connections. A friendly chat can give you insider info and might just get your foot in the door.

✨Tip Number 2

Show off your skills! Prepare a portfolio or a GitHub repository showcasing your data engineering projects. This is your chance to demonstrate your expertise in building data pipelines and working with cloud technologies.

✨Tip Number 3

Ace the interview! Research common data engineering interview questions and practice your answers. Be ready to discuss your experience with SQL Server, Azure, and any relevant tools like Databricks or Snowflake.

✨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 LexisNexis team.

We think you need these skills to ace Data Engineer II

SQL Server
Cloud-based Data Lakes (Azure and/or AWS)
Data Engineering
Production-grade Pipelines
Databricks
Snowflake
Azure Synapse
Redshift
Spark
Data Pipelines for AI/ML Workloads
Scrum
Kanban
Agile Software Development
DataOps Principles
API Design and Maintenance

Some tips for your application 🫡

Tailor Your Application: Make sure to customise your CV and cover letter for the Data Engineer II role. Highlight your experience with SQL Server, cloud-based Data Lakes, and any relevant projects that showcase your skills in building production-grade pipelines.

Showcase Your Technical Skills: Don’t hold back on detailing your technical expertise! Mention your hands-on experience with tools like Databricks, Spark, and any familiarity with MLOps workflows. This is your chance to shine, so let us know what you can bring to the table!

Be Clear and Concise: When writing your application, keep it clear and to the point. Use bullet points where possible to make it easy for us to see your qualifications at a glance. We appreciate straightforward communication!

Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy to do!

How to prepare for a job interview at LexisNexis

✨Know Your Data Engineering Stuff

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 building production-grade data pipelines and how you've tackled challenges in modern Data Engineering.

✨Showcase Your Collaboration Skills

Since you'll be interfacing with data scientists and AI engineers, it's crucial to demonstrate your ability to work in a team. Prepare examples of past projects where you collaborated effectively, focusing on how you gathered requirements and enabled production-ready AI use cases.

✨Get Familiar with the Tools

Dive into the specifics of tools like Databricks, Snowflake, and Azure Synapse. Be prepared to discuss how you've used these technologies in your previous roles, particularly in building scalable data ingestion and ML pipelines.

✨Understand Agile Methodologies

LexisNexis values Agile practices, so make sure you can talk about your experience with Scrum and Kanban. Share how these methodologies have influenced your work processes and contributed to successful project outcomes.

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