At a Glance
- Tasks: Build and maintain data pipelines while developing data models for analytics.
- Company: Join a forward-thinking firm prioritising data-driven decision making.
- Benefits: Flexible hours, mentorship, and opportunities for skill development.
- Other info: Collaborative team culture with a focus on innovation and growth.
- Why this job: Kickstart your Data Engineering career in a supportive, high-quality environment.
- Qualifications: Strong SQL skills and a passion for data modelling.
The predicted salary is between 30000 - 40000 £ per year.
Working week: Monday - Friday
Department: Information & Technology
Purpose of job: We are looking for a Data Engineer to join our growing Data team, supporting the development of our firm-wide data platform. Our platform is a central component of our organisation's business strategy, set and endorsed by our leadership board to put data at the heart of our decision making. This role is ideally suited to someone early in their Data Engineering career who has strong SQL and data modelling fundamentals, and is looking to further develop their skills within a structured, high-quality data environment.
You will work closely with our wider Data team with mentorship and guidance, contributing to the design, build, and maintenance of data pipelines and data models that underpin reporting and analytics across the firm.
Main Duties and Responsibilities:
- Build and maintain data pipelines to ingest and transform data from core business systems
- Develop and refine data models to support reporting, analytics, and insight generation
- Write efficient, reliable SQL transformations across the data platform
- Support the ingestion and structuring of new data sources
- Ensure high standards of data quality, consistency, and integrity
- Contribute to documentation, standards, and best practices across the data environment
- Work collaboratively with the wider Data team to deliver high-quality, production-ready outputs
- Identify opportunities to improve processes, performance, and reliability
Data Engineer (12 Month FTC) employer: Kingsley Napley LLP
Join a dynamic and innovative team as a Data Engineer, where you'll have the opportunity to develop your skills in a supportive environment that prioritises mentorship and collaboration. Our flexible working hours and commitment to high-quality data practices ensure that you can thrive both personally and professionally while contributing to our strategic vision of data-driven decision making. Located in a vibrant area, we offer a culture that values growth, inclusivity, and the pursuit of excellence, making us an exceptional employer for those looking to make a meaningful impact.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer (12 Month FTC)
✨Embrace Online Competitions
Get involved in online data science competitions like Kaggle or DrivenData. These platforms not only let you showcase your skills but also help you build a portfolio that stands out to hiring companies like Kingsley Napley LLP when you're aiming for that entry-level role.
✨Join Data Science Meetups
Look for local data science meetups or workshops happening in your area. These are perfect for connecting with industry professionals and fellow newbies, giving us the chance to learn the ropes and get our foot in the door at companies like Kingsley Napley LLP.
✨Networking Through University Career Services
Don't forget to leverage your university's career services! They often have exclusive internships and networking events specifically for entry-level data science positions. This is a golden opportunity to meet recruiters from companies like Kingsley Napley LLP.
✨Spotlight Your Skills Online
Create a strong online presence by sharing your projects and insights on platforms like GitHub or LinkedIn. Make sure to apply directly through Kingsley Napley LLP’s career page, where your unique skills can shine in their entry-level data science openings!
We think you need these skills to ace Data Engineer (12 Month FTC)
Some tips for your application 🫡
Show Off Your Data Skills:As you're aiming for an entry-level data science role at Kingsley Napley LLP, don't forget to highlight your proficiency in programming languages like Python or R. Dive into your CV and mention any relevant projects or coursework that demonstrate your data analysis skills or machine learning knowledge.
Include Relevant Projects:If you've done any data-related projects, whether in your studies or during a personal quest, showcase them in a portfolio. This gives us a tangible sense of your capabilities and shows your hands-on experience with data manipulation, visualisation, or model building.
Tailor Your Cover Letter:When crafting your cover letter, make sure to express your enthusiasm for data science and how this role at Kingsley Napley LLP aligns with your career goals. Consider sharing why you’re drawn to data-driven decision-making and how you see yourself growing in this field.
Show Your Curiosity:In the data science world, curiosity is key! Mention any online courses or certifications you've pursued that complement your studies. This could be anything from a statistics certification to a data visualisation workshop. It shows us you're serious about learning and growing in this field.
How to prepare for a job interview at Kingsley Napley LLP
✨Brush Up on Your Statistics
For a data science role, the interview may involve some statistical questions or problems. Make sure you're comfortable with concepts like probability, distributions, and hypothesis testing. This will not only help you answer questions but also show your analytical thinking.
✨Get Hands-On with Tools
Familiarise yourself with popular data science tools like Python, R, and SQL. If you're asked about specific projects, be ready to discuss the tools you used and how they contributed to your analysis. Showing that you not only know the theory but can apply it is essential!
✨Showcase Relevant Projects
As an entry-level candidate, your portfolio is crucial. Bring along examples of data projects you've worked on, whether during your studies or personal projects. Discuss the challenges you faced and how you overcame them, highlighting your problem-solving skills.
✨Prepare for Case Studies
Entry-level interviews in data science often include case studies where you'll have to analyse a dataset or solve a problem on the spot. Try out some practice case studies beforehand, so you're not caught off guard. It's all about displaying your thought process and how you tackle data-driven challenges!
