At a Glance
- Tasks: Lead the development of a cutting-edge data platform using Databricks, Python, and PySpark.
- Company: Join LexisNexis, a digital pioneer transforming legal and business information globally.
- Benefits: Enjoy flexible hours, generous holidays, health benefits, and extensive learning resources.
- Why this job: Be at the forefront of data innovation while mentoring a dynamic team in a collaborative environment.
- Qualifications: Expertise in Python, PySpark, and cloud platforms is essential; leadership experience is a must.
- Other info: Work-life balance is prioritized with numerous wellbeing initiatives and volunteer opportunities.
The predicted salary is between 43200 - 72000 £ per year.
About our Team The Content Engineering teams at LexisNexis Intellectual Property (IP) are at the forefront of innovation, transforming the way patent data is processed, managed, and utilized. We are in the initial stages of building our DataOps team who will govern the Data Quality across the entire technology department. Our teams are working closely with Databricks to migrate existing ETL solutions to a state-of-the-art Databricks, Python and PySpark tooling that will become our new Strategic Data Platform. The Data Platform ingests, processes, and enriches patent information from multiple global authorities using a medallion architecture. About the Role As the technical lead for the team building the strategic Data Platform at LexisNexis IP, you will be instrumental in executing our data strategy for the Data Platform. Your role will be pivotal in developing and implementing advanced solutions for data integration, quality control, and continuous delivery, driving our data operations to new heights. Your expertise will be crucial in embedding best practices and state-of-the-art data engineering tools, ensuring that our workflows are both efficient and scalable. Responsibilities Architecting and leading the development of our patent data ingestion pipeline using Databricks, Python, and PySpark. Mentoring and guiding a team of data engineers, fostering a collaborative environment that encourages growth and innovation. You will enable and lead technical discussions within the team and with stakeholders Ensuring the pipeline is efficient, scalable, and robust, capable of handling terabytes of data with low latency. Eliminate inefficiencies and teach the techniques to the team. Contributing to the overall data engineering strategy and drive the adoption of best practices in coding, architecture, and deployment. Identifying and resolving technical challenges, ensuring the smooth operation of the data ingestion pipeline. Automating the boring stuff, and make space for the team to tackle the most challenging up and coming problems. Requirements Demonstrate expertise in Python, and PySpark is essential for you to lead the skill up the team. Demonstrate expertise in Databricks would be highly desirable and advantageous. Demonstrate ability to design and implement scalable data architectures for both batch and streaming data processing. Demonstrate proficiency in using cloud platforms such as AWS, Azure, or Google Cloud for data infrastructure management Knowledge of data governance practices, including data quality management, metadata management, and data lineage Proven experience in leading and mentoring technical data engineering teams. 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 flexible hours – flexing the times when you work in the day to help you fit everything in and work when you are the most productive Working for you 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: 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.
Data Engineering Lead employer: LexisNexis Intellectual Property Solutions
Contact Detail:
LexisNexis Intellectual Property Solutions Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineering Lead
✨Tip Number 1
Familiarize yourself with Databricks, Python und PySpark, da diese Technologien für die Rolle entscheidend sind. Zeige in Gesprächen oder Netzwerken, dass du praktische Erfahrungen mit diesen Tools hast und bereit bist, dein Wissen im Team zu teilen.
✨Tip Number 2
Betone deine Fähigkeiten in der Architektur und Implementierung skalierbarer Datenarchitekturen. Bereite Beispiele vor, wie du in der Vergangenheit komplexe Datenpipelines entworfen und optimiert hast, um deine Eignung für die technische Leitung zu demonstrieren.
✨Tip Number 3
Zeige deine Erfahrung in der Führung und Mentoring von technischen Teams. Bereite dich darauf vor, konkrete Situationen zu diskutieren, in denen du andere unterstützt und gefördert hast, um ein kollaboratives Arbeitsumfeld zu schaffen.
✨Tip Number 4
Informiere dich über die besten Praktiken im Bereich Datenqualität und -governance. Diskutiere, wie du diese Prinzipien in früheren Projekten angewendet hast, um die Effizienz und Robustheit von Datenpipelines zu gewährleisten.
We think you need these skills to ace Data Engineering Lead
Some tips for your application 🫡
Understand the Role: Make sure to thoroughly read the job description for the Data Engineering Lead position. Understand the key responsibilities and required skills, especially around Databricks, Python, and PySpark.
Highlight Relevant Experience: In your CV and cover letter, emphasize your experience with data architecture, cloud platforms, and leading technical teams. Provide specific examples of projects where you have successfully implemented scalable data solutions.
Showcase Your Leadership Skills: Since the role involves mentoring and guiding a team, include details about your leadership style and any previous experience in mentoring or leading data engineering teams. Highlight how you foster collaboration and innovation.
Tailor Your Application: Customize your application materials to reflect the values and culture of LexisNexis. Mention your alignment with their commitment to wellbeing and work/life balance, as well as your enthusiasm for contributing to their data strategy.
How to prepare for a job interview at LexisNexis Intellectual Property Solutions
✨Showcase Your Technical Expertise
Make sure to highlight your experience with Python, PySpark, and Databricks during the interview. Be prepared to discuss specific projects where you've implemented these technologies, as well as any challenges you faced and how you overcame them.
✨Demonstrate Leadership Skills
As a Data Engineering Lead, you'll be expected to mentor and guide a team. Share examples of how you've successfully led teams in the past, focusing on fostering collaboration and innovation within your group.
✨Discuss Data Architecture Knowledge
Be ready to talk about your experience designing scalable data architectures for both batch and streaming data processing. Provide insights into your approach to ensuring data quality and governance practices.
✨Emphasize Problem-Solving Abilities
Prepare to discuss how you've identified and resolved technical challenges in previous roles. Highlight your ability to automate processes and eliminate inefficiencies, showcasing your proactive approach to improving data operations.