At a Glance
- Tasks: Design and develop cloud-based data systems for global market data delivery.
- Company: A growing financial data and analytics company with a collaborative culture.
- Benefits: Competitive salary, bonus, hybrid work model, and strong learning environment.
- Other info: Work in a supportive environment with opportunities for growth.
- Why this job: Join a dynamic team and make an impact in the financial data industry.
- Qualifications: 6+ years in Software/Data Engineering, strong Python and SQL skills.
The predicted salary is between 60000 - 80000 £ per year.
A growing financial data and analytics company is seeking a Software Engineer to join its Data Distribution team in London. The team is responsible for developing and maintaining platforms that deliver large-scale historical market data products to global customers.
Key Responsibilities
- Design, develop and maintain cloud-based data distribution systems
- Build scalable solutions to process and deliver terabytes of data daily
- Develop and improve CI/CD pipelines and workflow automation
- Support system reliability, performance and operational efficiency
- Work closely with product and operations teams on platform improvements
- Contribute to architecture, testing and deployment activities
Key Skills & Experience
- 6+ years of experience in Software Engineering or Data Engineering
- Strong Python and SQL development skills
- Experience building applications on AWS
- Understanding of distributed systems and cloud-based architectures
- Experience with Databricks and/or Snowflake
- Familiarity with Linux, Docker, Airflow and CI/CD tooling
- Strong communication and problem-solving skills
Desirable
- Experience with C++, C or Java
Additional Information
- Hybrid working model – 2 days per week in London office
- Strong collaborative culture and learning environment
- Competitive salary, bonus and benefits package
Data Software Engineer in London employer: TalentHawk
Join a dynamic financial data and analytics company in London, where innovation meets collaboration. As a Data Software Engineer, you'll thrive in a strong learning environment that values your growth, offering competitive salaries and a comprehensive benefits package. With a hybrid working model, you can enjoy the flexibility of remote work while being part of a team dedicated to delivering cutting-edge data solutions to global clients.
StudySmarter Expert Advice🤫
We think this is how you could land Data Software Engineer 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 TalentHawk!
✨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 Software Engineer at TalentHawk.
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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 TalentHawk.
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We think you need these skills to ace Data Software Engineer 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 TalentHawk, 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 TalentHawk. 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 TalentHawk
✨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 TalentHawk!
✨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.
