At a Glance
- Tasks: Build and maintain data pipelines that power marketing decisions and improve customer journeys.
- Company: Join LexisNexis Risk Solutions, a leader in risk assessment and data solutions.
- Benefits: Enjoy country-specific benefits that support your well-being and happiness.
- Other info: Be part of a diverse team committed to equal opportunity and professional growth.
- Why this job: Shape the future of marketing with trusted data and innovative technology.
- Qualifications: Experience in SQL, ETL frameworks, and cloud platforms like Azure or AWS.
The predicted salary is between 60000 - 80000 £ per year.
Are you passionate about building trusted customer data foundations that power meaningful marketing decisions? Would you like to shape scalable data pipelines and models that improve customer journeys, analytics, and business outcomes? LexisNexis Risk Solutions is the essential partner in the assessment of risk. Within our Business Services vertical, we offer a multitude of solutions focused on helping businesses of all sizes drive higher revenue growth, maximize operational efficiencies, and improve customer experience. Our solutions help our customers solve difficult problems in the areas of Anti-Money Laundering/Counter Terrorist Financing, Identity Authentication & Verification, Fraud and Credit Risk mitigation and Customer Data Management.
This role acts as the technical backbone for the Marketing Hub—partnering closely with analytics, MarTech, and digital teams to deliver the pipelines, data models, and governance frameworks that support personalisation, measurement, experimentation, and strategic decision‑making. The Data Engineer ensures data is not only accurate and compliant but designed for high performance and long‑term growth. The Data Engineer plays a foundational role in enabling modern, insight‑driven marketing by building and maintaining the data infrastructure that powers the organisation’s customer intelligence ecosystem. Working across the Customer Data Platform, journey orchestration capability, and advanced analytics and dashboarding environment, the role ensures that marketing has access to trusted, well‑structured, and scalable data.
Responsibilities
- Data Architecture & Pipeline Engineering: Build and maintain reliable pipelines integrating customer, campaign, and operational data into the CDP, ensuring accuracy and readiness for analysis.
- Marketing Data Model Design: Develop scalable models supporting segmentation, lifecycle analytics, attribution, and KPI frameworks.
- CDP Enablement & Identity Management: Partner with MarTech and Analytics to improve identity resolution, consent logic, and data quality within the CDP.
- Journey Orchestration Data Readiness: Enable event streams, triggers, and monitoring to support accurate, timely customer journeys.
- Analytics & Dashboarding Enablement: Provide structured datasets and semantic layers for reporting and dashboards, aligned with KPI frameworks.
- Data Governance & Quality Assurance: Maintain data quality, lineage, and compliance with GDPR and PII standards.
- Collaboration & Strategic Influence: Work closely with the Senior Marketing Analyst to align on priorities, translating technical concepts into business insights.
- Operational Excellence & Standards: Ensure scalable, stable data operations using best practices in automation, observability, and continuous improvement.
Requirements
- Advanced SQL, ETL/ELT frameworks, and cloud data platforms such as Azure, AWS, or GCP.
- Data modelling and pipeline orchestration using tools such as Airflow, Data Factory, dbt, or similar.
- Integrate CDP data sources across digital, CRM, transactional, and behavioural data; support identity resolution, consent handling, audience activation, journey events, trigger logic, and behavioural signals.
- Build data marts and semantic layers for dashboarding and BI tools such as Power BI or Tableau; structure datasets optimised for KPI frameworks, attribution, funnel, and lifecycle analytics.
- Apply data quality frameworks, lineage, cataloguing, and GDPR/PII compliance practices.
- Design secure data pipelines with monitoring, alerting, and SLA/SLO management.
- Translate business and marketing needs into clear technical specifications, communicating technical topics clearly to non‑technical stakeholders.
- Partner with analytics, marketing ops, and MarTech teams to own scalable, reliable, trusted customer‑data solutions.
We offer country-specific benefits that support your well‑being and happiness. We are an equal‑opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law.
Data Engineer employer: LexisNexis Risk Solutions
At LexisNexis Risk Solutions, we pride ourselves on being an exceptional employer that fosters a collaborative and innovative work culture. As a Data Engineer, you will have the opportunity to work with cutting-edge technologies in a supportive environment that encourages professional growth and development. Our commitment to employee well-being is reflected in our comprehensive benefits package and our dedication to diversity and inclusion, making us a great place for those looking to make a meaningful impact in the field of data engineering.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer
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We think you need these skills to ace Data Engineer
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!
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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!
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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.
