At a Glance
- Tasks: Transform and model data using SQL and Python to build efficient workflows.
- Company: Join Lendable, a leading fintech data platform with a focus on innovation.
- Benefits: Enjoy competitive pay, flexible work options, and opportunities for growth.
- Other info: Be part of a dynamic team driving the future of fintech data solutions.
- Why this job: Make an impact by creating scalable data products in a modern tech stack.
- Qualifications: Experience with Python, SQL, and data engineering principles required.
The predicted salary is between 63000 - 77000 £ per year.
Lendable is building one of the world's leading fintech data platforms and is expanding its Python Infrastructure team.
The role focuses on transforming and modelling data with SQL and dbt, while using Python to build workflows, automate processes, and create data tools that improve day-to-day work.
You will work across analytics engineering and data engineering, delivering reliable, scalable data products on a modern stack centered around Snowflake, dbt and Python.
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Data Engineer — Python, SQL & Data Pipelines in London employer: Lendable
Lendable is an exceptional employer that champions innovation and flexibility, making it an ideal place for a Senior Kotlin/JVM Engineer to thrive. With a vibrant work culture that prioritises collaboration and personal growth, employees are encouraged to develop their skills while contributing to impactful financial products. The company's commitment to flexible working arrangements further enhances the work-life balance, making it a rewarding environment for those looking to make a difference in the fintech space.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer — Python, SQL & Data Pipelines in London
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Lendable!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Data Engineer — Python, SQL & Data Pipelines at Lendable.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Lendable.
✨Apply Directly through Our Website
When you find a suitable opening like Data Engineer — Python, SQL & Data Pipelines at Lendable, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Data Engineer — Python, SQL & Data Pipelines in London
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!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Lendable, 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 Lendable. 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 Lendable
✨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!
✨Showcase Your Projects
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 Lendable!
✨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.
