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- Tasks: Lead the development of Python interfaces and integrations for cloud data sources.
- Company: Join a cutting-edge tech firm focused on high-performance applications.
- Benefits: Attractive salary, flexible working options, and opportunities for skill enhancement.
- Other info: Dynamic team environment with potential for rapid career advancement.
- Why this job: Be at the forefront of technology, shaping the future of data integration.
- Qualifications: Strong Python skills, experience with databases, and knowledge of cloud technologies.
The predicted salary is between 60000 - 80000 £ per year.
Development and support of the Python Native interface for KX (pykdb development, support, documentation).
Development of integrations for Connectors to cloud data sources (Kinesis, PubSub, Solace, MQTT, Azure Blob, GCP Cloud Storage, ...).
- C/C++
- Python
- Docker
- Cython is a significant plus.
- Q/kdb+ is a significant plus.
- Experience developing high-performance applications/algorithms in Python.
- Experience with databases and big data.
- Experience developing streaming applications is a plus (Flink, Spark Streaming, Beam, etc).
- Experience tracing, profiling, and benchmarking applications is a plus - especially in Python.
Python Lead employer: KX
Contact Detail:
KX Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Python Lead
✨Tip Number 1
Network like a pro! Reach out to folks in your industry on LinkedIn or at meetups. We all know that sometimes it’s not just what you know, but who you know that can land you that Python Lead role.
✨Tip Number 2
Show off your skills! Create a GitHub repository showcasing your Python projects, especially those involving high-performance applications or integrations with cloud data sources. This gives potential employers a taste of what you can do.
✨Tip Number 3
Prepare for the interview like it’s a coding challenge! Brush up on your Python algorithms and be ready to discuss your experience with databases and big data. We want to see how you think and solve problems on the spot.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Python Lead
Some tips for your application 🫡
Show Off Your Python Skills: Make sure to highlight your experience with Python, especially in high-performance applications. We want to see how you've tackled challenges and what cool projects you've worked on!
Integrate Your Experience: If you've developed integrations for cloud data sources or have experience with streaming applications, let us know! We love seeing how you can connect the dots between different technologies.
Be Clear and Concise: When writing your application, keep it straightforward. We appreciate clarity, so avoid jargon unless it's necessary. Make it easy for us to see why you're a great fit!
Apply Through Our Website: Don't forget to submit your application through our website! It’s the best way for us to receive your details and ensures you’re considered for the role.
How to prepare for a job interview at KX
✨Know Your Python Inside Out
Make sure you brush up on your Python skills, especially around the native interface and high-performance applications. Be ready to discuss your past projects and how you've tackled challenges in Python development.
✨Familiarise Yourself with Cloud Integrations
Since the role involves developing integrations for various cloud data sources, it’s crucial to understand how Kinesis, PubSub, and others work. Prepare examples of any relevant experience you have with these technologies.
✨Showcase Your Big Data Experience
If you've worked with databases or big data technologies, be sure to highlight this during the interview. Discuss specific projects where you’ve implemented solutions using tools like Flink or Spark Streaming.
✨Prepare for Technical Questions
Expect to face questions about tracing, profiling, and benchmarking applications in Python. Brush up on these topics and be ready to explain your approach to optimising performance in your previous work.