Senior Data Engineer
WorldQuant
Job Overview
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Job Description
About WorldQuant
WorldQuant develops and deploys systematic financial strategies across a broad range of asset classes and global markets. We seek to produce high-quality predictive signals (alphas) through our proprietary research platform to employ financial strategies focused on market inefficiencies. Our teams work collaboratively to drive the production of alphas and financial strategies – the foundation of a balanced, global investment platform.
WorldQuant 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. Excellent ideas come from anyone, anywhere. Employees are encouraged to challenge conventional thinking and possess an attitude of continuous improvement.
Our goal is to hire the best and the brightest. We value intellectual horsepower first and foremost, and people who demonstrate an outstanding talent. There is no roadmap to future success, so we need people who can help us build it.
Technologists at WorldQuant research, design, code, test and deploy firmwide platforms and tooling while working collaboratively with researchers and portfolio managers. Our environment is relaxed yet intellectually driven. We seek people who think in code and are motivated by being around like-minded people.
The Role: Senior Data Engineer
We are looking for an experienced Python developer who will help us to build and maintain an ecosystem for processing multiple datasets from different sources (both internal and external) vital to the firm’s investment operations.
Key Responsibilities
- Creating optimized and fault-tolerant data processing pipelines
- Developing interfaces and micro services in Python
- Developing efficient algorithms for data processing
- Testing and integrating external APIs
- Enriching company’s data
- Implementing data cleansing, transformation, and validation to ensure data integrity and quality
- Monitoring and maintaining the health and performance of webservices and databases
- Troubleshooting and resolving data processing issues
What You’ll Bring
- A bachelor / master's degree in a technical or quantitative field from top university
- At least 3 years of experience as a data engineer or software developer
- Excellent programming skills
- Experience with data processing using Python
- Experience with building databases
- Experience with Containers and Kubernetes
- Scripting skills in UNIX environment: shell, python Fire, etc.
- Experience with code versioning tools (e.g. Git), issue tracking tools (e.g. Jira)
- Debugging skills, eye for detail and identifying problems
- Strong problem-solving skills and an analytical mindset
- A passion for working with data
What We Offer
- Competitive compensation package
- Core benefits include: premium private health insurance and life insurance with savings plan
- Support for every aspect of life through Employee Assistance Program and fully covered sick leave
- Strong culture of learning and development: training courses, library, guest speakers, share and learn events, global conferences
- Regular offsite team buildings, annual conferences and occasional global summits – opportunity to travel and connect with our local and global teams
Key skills/competency
- Python
- Data Processing
- ETL
- SQL
- APIs
- Kubernetes
- UNIX Scripting
- Git
- Data Integrity
- Problem Solving
How to Get Hired at WorldQuant
- Research WorldQuant's culture: Study their mission, values, recent news, and employee testimonials on LinkedIn and Glassdoor.
- Tailor your resume: Highlight Python, data engineering, and financial domain experience for the Senior Data Engineer role.
- Showcase problem-solving skills: Prepare examples demonstrating analytical thinking, debugging capabilities, and data pipeline optimization.
- Master technical fundamentals: Focus on data processing, algorithms, database management, and containerization with Kubernetes.
- Demonstrate passion for data: Articulate your interest in quantitative finance and solving complex data challenges effectively.
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