At a Glance
- Tasks: Own data architecture and optimise pipelines using Python and Airflow.
- Company: Dynamic FinTech scaling rapidly with a focus on innovation.
- Benefits: Competitive salary up to £130k, bonuses, and hybrid working.
- Other info: Collaborative environment with excellent career progression opportunities.
- Why this job: Shape the future of data engineering in a growing company.
- Qualifications: Strong Python skills and experience with data pipelines and governance.
The predicted salary is between 130000 - 130000 £ per year.
Senior Data Engineer (Python Airflow) London / WFH to 130k Are you a highly technical Data Engineer with Fin Tech / finance experience looking for an opportunity to progress your career?You could be progressing your career in a senior, hands-on Data Engineer role at a scaling Fin Tech, the core product is a private equities / alternative investment management platform.
As a Senior Data Engineer you'll take ownership of the data architecture, defining how data is structured, stored, transformed and made accessible across the business.
You'll build and optimise data pipelines, primarily using Airflow, while establishing robust data governance frameworks covering data ownership, access policies, residency requirements and standards.
Working across the company's international operations, you'll ensure data is managed appropriately across different regions, taking into account varying regulatory and data residency requirements.
You'll work closely with senior stakeholders, leading discussions around data ownership, architecture, storage and usage, while identifying opportunities to improve the performance, efficiency and scalability of the existing data infrastructure.
You'll also play a key role in shaping the future of data engineering as the business grows, exploring improved approaches to dataset replication and environment management, alongside modern CI/CD practices to streamline the deployment, maintenance and ongoing development of data engineering processes.
Location / WFH: You'll join colleagues in the London office three days a week with flexibility to work from home the other two days.
About you: You have a strong traditional data engineering background You have strong Python coding skills You have experience of building and optimising data pipelines You have strong experience with Apache Airflow or similar orchestration technologies You have experience with CI/CD and modern software engineering practices You have a good understanding of data architecture, modelling, transformation and storage You have experience with data governance and data ownership You have an understanding of data residency and the challenges of managing data across different geographies You're collaborative and pragmatic with communication skills What's in it for you: Salary to 130k + bonus Impactful role with excellent career progression Hybrid working (x3 days in London)Apply now to find out more about this Senior Data Engineer (Python Airflow) opportunity.
Senior Data Engineer - FinTech employer: Client Server
Join a dynamic and innovative FinTech company that values technical expertise and offers a collaborative work culture. With a competitive salary of up to £100k plus bonuses, you'll have the opportunity to make a significant impact while enjoying hybrid working arrangements in London. The company prioritises employee growth, providing ample opportunities for career progression and staying at the forefront of emerging technologies in the finance sector.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Engineer - FinTech
✨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 Client Server!
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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 Senior Data Engineer - FinTech at Client Server.
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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 Client Server.
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We think you need these skills to ace Senior Data Engineer - 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 Client Server, 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 Client Server. 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 Client Server
✨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 Client Server!
✨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.
