Python Software/Data Engineer

Python Software/Data Engineer

Full-Time Home office (partial)
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At a Glance

  • Tasks: Join a top-tier team to develop a cutting-edge data ingestion platform using OO Python.
  • Company: Work with a leading Quant Trading firm known for innovation and high performance.
  • Benefits: Enjoy a competitive salary, flexible work options, and a vibrant office culture.
  • Why this job: Be part of a dynamic environment with no legacy work and state-of-the-art technology.
  • Qualifications: 4+ years in OO Python and finance, plus experience in large-scale data pipelines.
  • Other info: Refer a friend for a chance to earn rewards through our referral scheme!

Job Description

Software/Data Developer – Market leading HFT/Systematic Trading Firm.

Compensation: Up to £250k TC

Location: London

WFH: 4 days in office, 1 from home

I'm currently working with one of the most successful and modern Quant Trading firms in London. Being a top 3 performer across various markets and boasting yearly returns of over 20%, they are have brought in some of the worlds best engineers of the past decade. Their modern and innovative approach means no legacy work to deal with and state of the art tech.

They're looking for a data focused Python Engineer to join one of their highest performing and unique teams, focusing on the development of a greenfield data ingestion platform, you will use OO Python to build out the backend of this platform and the associated large scale ETL pipelines with it. This is a fantastic opportunity for a top tier developer at the intersection of Software Development and Data Engineering.

Must Have

  • 4+ years experience in OO Python development
  • 4 + years experience in finance
  • 2+ years experience building out large scale data pipelines

Please contact james.griffin@stanfordblack.com for more information

  • If this role isn't right for you, but you know of someone who might be interested, we have a market-leading referral scheme in place to thank anyone who refers a friend who is successfully placed! T&Cs apply

Python Software/Data Engineer employer: Stanford Black Limited

Join a market-leading HFT/Systematic Trading firm in London, renowned for its innovative approach and exceptional performance. With a strong focus on employee growth, you will work alongside some of the brightest minds in the industry, utilising state-of-the-art technology to develop cutting-edge data solutions. Enjoy a flexible work culture with 4 days in the office and 1 day from home, alongside competitive compensation and a rewarding environment that fosters creativity and collaboration.
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Contact Detail:

Stanford Black Limited Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Python Software/Data Engineer

✨Tip Number 1

Network with professionals in the finance and tech sectors. Attend industry meetups or webinars where you can connect with current employees at trading firms. This can give you insights into their work culture and potentially lead to referrals.

✨Tip Number 2

Showcase your Python skills through personal projects or contributions to open-source projects. Having a portfolio that demonstrates your ability to build data pipelines or backend systems will make you stand out during interviews.

✨Tip Number 3

Stay updated on the latest trends in data engineering and quantitative trading. Familiarise yourself with tools and technologies commonly used in the industry, such as ETL frameworks, to discuss them knowledgeably during your interview.

✨Tip Number 4

Prepare for technical interviews by practising coding challenges that focus on Python and data structures. Websites like LeetCode or HackerRank can help you refine your problem-solving skills, which are crucial for this role.

We think you need these skills to ace Python Software/Data Engineer

Object-Oriented Programming (OOP) in Python
Data Pipeline Development
ETL (Extract, Transform, Load) Processes
Financial Data Analysis
Software Development Best Practices
Version Control (e.g., Git)
Database Management (SQL and NoSQL)
Data Modelling
Performance Optimisation
Problem-Solving Skills
Collaboration and Teamwork
Agile Methodologies
Cloud Technologies (e.g., AWS, Azure)
Data Warehousing

Some tips for your application 🫡

Tailor Your CV: Make sure your CV highlights your experience in OO Python development and finance. Emphasise any projects where you've built large scale data pipelines, as this is crucial for the role.

Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for data engineering and software development. Mention specific examples of your work that align with the job description, particularly your experience with data ingestion platforms.

Showcase Relevant Skills: In your application, clearly outline your technical skills related to Python and data engineering. Include any relevant tools or technologies you’ve used in past roles that would be beneficial for this position.

Proofread Your Application: Before submitting, carefully proofread your application for any spelling or grammatical errors. A polished application reflects your attention to detail, which is essential in a data-focused role.

How to prepare for a job interview at Stanford Black Limited

✨Showcase Your Python Expertise

Make sure to highlight your experience with OO Python development. Be prepared to discuss specific projects where you've implemented Python solutions, especially in the context of data engineering and large-scale ETL pipelines.

✨Demonstrate Financial Knowledge

Since the role requires experience in finance, brush up on relevant financial concepts and how they relate to data engineering. Be ready to explain how your background in finance has influenced your approach to software development.

✨Prepare for Technical Questions

Expect technical questions that assess your problem-solving skills and understanding of data ingestion platforms. Practice coding challenges or system design questions that are relevant to building scalable data pipelines.

✨Ask Insightful Questions

Prepare thoughtful questions about the company's technology stack, team dynamics, and the specific challenges they face in developing their data ingestion platform. This shows your genuine interest in the role and helps you gauge if it's the right fit for you.

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