Our Client develops and deploys systematic financial strategies across a variety of asset classes and global markets. They seek to produce high-quality predictive signals (alphas) through a proprietary research platform to employ financial strategies focused on exploiting market inefficiencies. The teams work collaboratively to drive the production of alphas and financial strategies – the foundation of a sustainable, global investment platform. Technologists research, design, code, test, and deploy projects while working collaboratively with researchers and portfolio managers. An environment is relaxed yet intellectually intense. Teams are lean and agile, which means rapid prototyping of products with immediate user feedback. We seek people who think in code, aspire to solve undiscovered computer science challenges, and are motivated by being around like-minded people. In fact, in the client company, approximately 500 employees code daily. Client’s success is built on a culture that pairs academic sensibility with accountability for results. Employees are encouraged to think openly about problems, balancing intellectualism and practicality. Great ideas come from anyone, anywhere. Employees are encouraged to challenge conventional thinking and possess a mindset of continuous improvement. That’s a key ingredient in remaining a leader in any industry. A goal is to hire the best and the brightest. Intellectual horsepower, first and foremost, and people who demonstrate an exceptional talent are valuable. There is no roadmap to future success, so we need people who can help us create it. Our collective intelligence will drive us there.
The Role:
We are looking for an experienced Python developer who will help our client build and maintain various internal tools and scripts to support vendor changes, data monitoring, and data quality efforts.
Key Responsibilities:
- Creating tools and scripts based on requirements from the business team;
- Testing and integrating external APIs;
- Monitoring and maintaining the health and performance of the tools and databases;
- Troubleshooting and resolving issues.
Requirements:
- A bachelor's/master's degree in a technical or quantitative field from a top university;
- At least 3 years of experience as a data engineer or software developer;
- Strong problem-solving skills and an analytical mindset;
- Excellent programming skills;
- Experience with data processing using Python;
- Experience with databases, at least SQL ones;
- Scripting skills in a UNIX environment;
- Debugging skills, eye for detail, and identifying problems;
- A passion for working with data.
Technical Skills (Mandatory):
- Proficient in Python and Logical Programming: Extensive experience with core Python libraries (requests, pandas, numpy, json, pyplot, etc.) and frameworks, coupled with a strong ability to apply logical reasoning and develop efficient algorithms to solve complex programming problems;
- PySpark: Experience with distributed data processing using PySpark;
- Strong Bash/Linux Skills: Comfortable navigating the command line, writing shell scripts, and managing files/permissions;
- Experience working with APIs: Familiarity with RESTful APIs, API authentication, and data serialization formats (e.g., JSON, XML);
- Proficient with Git: Experience with branching, merging, pull requests, and conflict resolution;
- CI/CD Proficiency: Hands-on experience implementing and managing CI/CD pipelines. Experience with GitLab Runner is a plus.
Technical Skills (Nice to Have):
- SQL and Database Experience: Familiarity with relational databases and writing SQL queries;
- Mathematical/Statistical Skills: Ability to analyze data, identify trends, and draw meaningful conclusions;
- Airflow: Experience with workflow orchestration and scheduling using Airflow;
- AI/LLM for Automation: Interest in and experience with applying AI and Large Language Models to automate processes.
Soft Skills (Required):
- Proactive Problem Solver: Demonstrates initiative and takes ownership of challenges;
- Excellent Communication Skills: Communicates effectively both verbally and in writing;
- Strong Technical Writing Skills: Emphasis on writing clear and concise documentation for both the code itself and the overall implementation process;
- Research Mindset: Embraces working with unknowns and proactively explores solutions.
Last Updated: June, 2025
