Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Data Engineer III

RELX Group
City of London
4 days ago
Create job alert
Overview

At LexisNexis Intellectual Property (LNIP), our mission is to bring clarity to innovation by delivering better outcomes to the innovation community. We help innovators make more informed decisions, be more productive, and ultimately achieve superior results. By helping our customers achieve their goals, we support the development of new technologies and processes that ultimately advance humanity. As a Data Engineer at LexisNexis Intellectual Property (LNIP), you will be designing, building, and maintaining complex data systems to support business needs. Utilizing your expertise, youll contribute to maintaining a Data Platform that serves our crucial and critical product. Your role will be critical in ensuring the integrity, security, and accessibility of business-critical data.

Responsibilities
  • Be a hands-on Data Engineer working across our ecosystem of products and Data Platforms.
  • Interface with other technical personnel or team members to finalize requirements.
  • Developing and maintaining data infrastructure supporting real-time data processing in streaming architectures.
  • Implementing scalable data ingestion and ML pipelines, incorporating Data Lakehouse concepts for unified data management
  • Successfully implement development processes, coding best practices, and code reviews.
  • Designing APIs for diverse business units, ensuring efficient data lineage tracking
  • Utilizing DataOps principles to enhance system performance and reliability.
  • Automating system lifecycle management, ensuring robustness and scalability
  • Integrating advanced data engineering techniques and tools to streamline processes.
  • Resolve technical issues as necessary.
  • Keep abreast of new technology developments.
  • Experience in SQL Server, Data Lake (Azure/AWS).
  • Possess extensive modern Data Engineering experience.
  • Demonstrate in-depth knowledge of large-scale data platforms (Databricks, Snowflake) and cloud-native tools (Azure Synapse, RedShift).
  • Knowledge of software development methodologies including Scrum, Kanban, and Agile more broadly.
  • Experience of analytics technologies (Spark, Hadoop, Kafka).
  • Experience with test-driven development.
Nice to have
  • Understanding of Elasticsearch, Solr, PostgreSQL, Databricks, Delta Share & Delta Lake.
  • Ability to work with complex Patent and Litigation data models.
  • Ability to work well with internal and external technology data resources, including DocDB, ESpacenet & USPTO.
  • Experience with Pandas & PySpark.
Work style

Work in a way that works for you.

About LexisNexis Intellectual Property

LexisNexis Intellectual Property, which serves customers in more than 150 countries with 11,300 employees worldwide, is part of RELX, a global provider of information-based analytics and decision tools for professional and business customers. LexisNexis Legal & Professional A9 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 AE and Nexis AE services.

Benefits and work environment

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. Flexible working hours are available to help you fit responsibilities and peak productivity. We are committed to your wellbeing and happiness as key to a long and successful career. Benefits include:

  • 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.


#J-18808-Ljbffr

Related Jobs

View all jobs

Data Engineer III

Data Engineer III

Data Engineer III

Data Engineer III

Data Engineer III- Python & AWS

Data Engineer III- Python & AWS

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Data Science Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK data science hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise rigorous problem framing, high‑quality analytics & modelling, experiment/causality, production awareness (MLOps), governance/ethics, and measurable product or commercial impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for product/data scientists, applied ML scientists, decision scientists, econometricians, growth/marketing analysts, and ML‑adjacent data scientists supporting LLM/AI products. Who this is for: Product/decision/data scientists, applied ML scientists, econometrics & causal inference specialists, experimentation leads, analytics engineers crossing into DS, ML generalists with strong statistics, and data scientists collaborating with platform/MLOps teams in the UK.

Why Data Science Careers in the UK Are Becoming More Multidisciplinary

Data science once meant advanced statistics, machine learning models and coding in Python or R. In the UK today, it has become one of the most in-demand professions across sectors — from healthcare to finance, retail to government. But as the field matures, employers now expect more than technical modelling skills. Modern data science is multidisciplinary. It requires not just coding and algorithms, but also legal knowledge, ethical reasoning, psychological insight, linguistic clarity and human-centred design. Data scientists are expected to interpret, communicate and apply data responsibly, with awareness of law, human behaviour and accessibility. In this article, we’ll explore why data science careers in the UK are becoming more multidisciplinary, how these five disciplines intersect with data science, and what job-seekers & employers need to know to succeed in this transformed field.

Data Science Team Structures Explained: Who Does What in a Modern Data Science Department

Data science is one of the most in-demand, dynamic, and multidisciplinary areas in the UK tech and business landscape. Organisations from finance, retail, health, government, and beyond are using data to drive decisions, automate processes, personalise services, predict trends, detect fraud, and more. To do that well, companies don’t just need good data scientists; they need teams with clearly defined roles, responsibilities, workflows, collaboration, and governance. If you're aiming for a role in data science or recruiting for one, understanding the structure of a data science department—and who does what—can make all the difference. This article breaks down the key roles, how they interact across the lifecycle of a data science project, what skills and qualifications are typical in the UK, expected salary ranges, challenges, trends, and how to build or grow an effective team.