At a Glance
- Tasks: Design and build scalable SQL databases and manage cloud-based data solutions.
- Company: Fast-growing fintech tech company focused on data and machine learning.
- Benefits: Comprehensive health package, tech stipend, learning budget, and flexible working options.
- Other info: Enjoy quarterly adventure days and a culture that values mental health and innovation.
- Why this job: Join a dynamic team and shape the future of fintech with innovative data solutions.
- Qualifications: 5+ years in data engineering, strong SQL skills, and experience with Azure.
The predicted salary is between 63000 - 77000 £ per year.
Описание
The client is an innovative, fast-growing technology company operating across data, cloud, and machine learning.
It builds scalable, data-driven platforms that support advanced analytics and AI-powered applications across fintech, healthcare, and digital services.
- Задачи
- Design and build SQL databases from scratch for scalability, reliability, and performance
- Optimise and maintain existing database systems to improve query performance and efficiency
- Architect, implement, and manage cloud-based databases and data solutions in Azure
- Develop and maintain data pipelines for analytics and machine learning workloads
- Collaborate with data scientists to prepare and structure data for ML modelling
- Contribute to Python-based machine learning models and data processing workflows
- Ensure best practices in data governance, security, and integrity
- Work with cross-functional teams to understand data requirements and deliver scalable data solutions
- Требования
- 5+ Years of experience in data engineering or database development roles
- Strong expertise in SQL and relational database design, including schema design, indexing, and optimisation
- Experience building and managing databases from the ground up
- Hands-on experience with Microsoft Azure data services such as Azure SQL, Data Factory, and Synapse
- Proficiency in Python for data processing and basic machine learning workflows
- Solid understanding of data modelling, ETL processes, and data architecture principles
- Experience with performance tuning and query optimisation
- Strong problem-solving skills and attention to detail
- Nice to have: experience with big data tools or distributed data systems, familiarity with ML frameworks such as scikit-learn, Tensor Flow, and Py Torch, knowledge of data warehousing concepts and modern data stack tools, exposure to Dev Ops practices, CI/CD, or infrastructure-as-code, experience in fast-paced or startup environments
- Условия
- Comprehensive Health & Wellness Package, including mental health support
- Tech Upgrade Stipend for home setup
- Learning & Development Budget for courses, certifications, and conferences
- Quarterly Innovation Days to explore new ideas and technologies
- One paid Adventure Day per quarter
- Gym access, wellness initiatives, and encouraged mental health days
- Flexible working options
- #J-18808-Ljbffr
data engineer in fintech employer: Enfint
AJ Bell is an exceptional employer that fosters a collaborative and innovative work culture in the heart of London. With a strong emphasis on employee growth, you will have the opportunity to mentor junior designers while working on impactful design systems that prioritise accessibility and usability. Enjoy a supportive environment that values proactive communication and offers unique benefits tailored to enhance your professional journey.
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We think this is how you could land data engineer in fintech
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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 Enfint!
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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 Enfint.
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We think you need these skills to ace data engineer in fintech
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 Enfint, 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 Enfint. 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 Enfint
✨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 Enfint!
✨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.
