Senior Developer

Job Purpose

The New York Stock Exchange, a subsidiary of Intercontinental Exchange, Inc. (ICE) presents an opportunity for a full-time Senior developer to join a team responsible for development of data analytics workflows. The Senior Developer will have experience in all phases of software development lifecycle, from requirements gathering, to design, coding, unit testing, debugging, and supporting in production.

The candidate will be part of a highly visible team responsible for ingesting and analyzing large quantities of trading data at NYSE. The ideal candidate should be knowledgeable in data processing, database systems and scripting languages.

This position requires technical proficiency/problem solving as well as an eager attitude, professionalism, and solid communication skills. Strong written and oral communication is required as the applicant will frequently be interacting with different teams across NYSE to achieve business goals.

Responsibilities

On any day, the candidate could be doing any or all of the following:

• Work closely with teams across NYSE Regulation developing and maintaining surveillances
• Analyze requirements and propose technical solutions in delivering projects within expected parameters of cost, time, and quality.
• Data format conversion to make it more appropriate for analysis.
• Create experimental and new frameworks to collect data as well as build tools to automate data collection.
• Optimizing the SQL queries for performance
• Search through large sets of data for meaningful information.
• Creating reports and presentations for business use cases.
• Use statistical tools to identify, analyze, and interpret patterns and trends in complex data sets that could be helpful for the diagnosis and prediction.
• Develop and maintain databases, data systems - reorganizing data in a readable format.
• Work with project managers to compile a work breakdown structure of tasks for a given deliverable and provide realistic estimates for completing the assignment.
• Develop and unit test all functions created or modified according to software development best practices.
• Collaborate with other Developers and QA Engineers to execute full cycle integration, functional and regression testing.
• Continuously improve the system performance and propose better solutions.
• Effectively interact with business and operations for solving design and operational challenges.
• Brainstorm identifying ML/AI/NLP innovations to apply in quantitative analysis on market microstructure and in surveillance to help in advance automation, knowledge discovery, decision-making and insights.
• Implement and prototype new algorithms and write code for novel ML/AI/NLP/LLM solutions.

Knowledge and Experience

• Bachelor's degree in computer science, data science, finance or mathematics with a minimum of five years of experience.
• Strong, proven programming skills in Python, Java, R, MATLAB, or Scala.
• Strong knowledge of SQL and Python libraries used for data science.
• SQL Query tuning using different tools. Clear understanding of query plan management.
• Experience in timeseries database
• Experience in Spark SQL and PARQUET.
• Experience in data visualization and business analytics tools like Alteryx, Tableau and Microsoft PowerBI is a plus.
• Experience in Databricks/Snowflake is a plus.
• Experience in scripting languages like AWK/bash shell scripting is beneficial.
• Experience working in Agile teams comprised of 5-8 cross-skilled engineers.
• Solid understanding of version control tools (ideally Git).
• Experience applying data-driven statistical analysis and modeling to financial market data.
• Experienced in writing complex programs and implementing custom algorithms.
• Expertise in tailoring open-source frameworks to specific needs by writing custom code that integrates seamlessly.
• Experience in data management, data analytics middleware, platforms and infrastructure, cloud and fog computing are a plus.
• Additional experience working in cloud environments such as AWS is desirable.
• Excellent communication skills (oral and written) to explain complex algorithms, solutions to stakeholders across multiple disciplines, and ability to work in a diverse team.
• Experience in an applied R&D environment, working in an agile and innovation-lab culture.