A.P.T Portfolio is a high frequency trading firm that specializes in Quantitative Trading & Investment. The Data Engineering team works on the integration, consolidation, management and analysis of the different kinds of data that is collected from the firm's trading activities and different exchanges we trade with. The team also works on developing the firm's quantitative research, modeling and high-performance computing infrastructure for back-testing and simulations of strategies. 

You will be part of a team that is intellectually curious, creative, analytical, and passionate about building complex data infrastructure and digging into data for analysis and/or market research.

Core Responsibilities:  

• Working with our core Data APIs / Platform Software 
• Development and Improvement of automated Pipelines for processing global Exchange Market Data 
• Develop expertise in working with Tabular, Columnar and OLAP Databases 
• Design and implement performance, scalability, stability, and stress tests using industry standard tools, and custom solutions. 
• Benchmark Production and Test Labs for base lining and ensure sanity of data and accuracy of test simulations
• Develop tools to simulate and monitor key performance metrics as needed. 
• Work on improvement and optimization of our Grid Computing System used for massively parallel compute and simulations. 
• Develop a deeper understanding of all kinds of data managed by the team including but not limited to market data, reference data, back office and account information, computed analytics, research metadata, etc. 
• Innovate and PoC around upcoming cutting edge tools and automation systems to improve the efficiency of the data pipelines. 
• Be involved in all other Python Infrastructure development efforts across the firm.

Required Qualification / Skill Set:  

• STEM degree with 2+ years of relevant work experience
• High proficiency in Python including Pandas and NumPy libraries
• Understanding of Python software architecture and development environments   
• A sense of testing frameworks in Python, and experience with test driven development.  
• Aptitude for algorithms, data structures, and software design 
• Experience with Linux operating system internals and/or networking concepts 
• Strong analytical skills, with an ability to quickly identify scope and impact of issues during high-pressure situations 
• Paranoid about automation and code optimization for low latency.