Software Engineer – Data Team

HBK Capital Management•Dallas, NY

9d•Onsite

About The Position

Help build technical infrastructure to drive data imports from third party vendors into multinational organization’s proprietary IT systems, including providing both traditional and alternative data sets to company’s staff members as well as working closely with front office traders, quantitative analysts and other investment professionals to improve company’s software development functions, such as data ingestion and IT-engineering analysis. Design, develop, and deploy Model Context Protocol (MCP) servers to connect Large Language Model (LLM) clients to internal organization tools and systems, including proprietary databases, Jira, Bloomberg, Confluence, and internal analytics servers, by independently exploring technical approaches, proposing end-to-end solutions, and implementing secure interfaces and workflows to enable automated tool execution, data retrieval, and enhanced productivity for internal technical and front office stakeholders. Maintain and enhance company’s platform and infrastructure by utilizing knowledge of Microsoft SQL Server and Python, including building visualization tools, analytical tests, and mathematical algorithms to show an overview of all the software and IT-backed systems owned by company’s Data Team. Assist IT-based technical teams in building systems to interface with third-party API’s asynchronously to facilitate data fetches. Integrate financial and alternative datasets for research and trading using Python, agile development methodologies and Object-Oriented Design (OOD) and development techniques to ensure the quality of pricing and reference data through the creation of manual and automated data integrity processes. Partner with front office analysts and quantitative analysts on both discretionary and systematic businesses, providing new software engineering ideas and enhancements to automate internal organization systems and data collection processes using SQL and No-SQL databases, as well as software tools/frameworks such as Hadoop, Spark, Redis, etc. Develop tools to enhance and streamline data used in client portfolio reviews by utilizing knowledge of User Interface (UI) development while concurrently on-boarding multiple datasets from different vendors and technical sources, including cleaning vendor data and normalizing same into organization’s software, IT systems, and databases. Perform troubleshooting or code inspection actions on internal systems for use by company traders, as well as providing adequate data search options for internal analysis tools.

Requirements

Master’s degree in Computer Science, Data Science or Software Engineering
Three (3) years of experience in job offered or three (3) years of data validation and analysis experience in a Python infrastructure environment

Responsibilities

Build technical infrastructure to drive data imports from third-party vendors into proprietary IT systems.
Provide traditional and alternative data sets to company staff.
Work closely with front office traders, quantitative analysts, and other investment professionals to improve software development functions, data ingestion, and IT-engineering analysis.
Design, develop, and deploy Model Context Protocol (MCP) servers to connect Large Language Model (LLM) clients to internal organization tools and systems (proprietary databases, Jira, Bloomberg, Confluence, internal analytics servers).
Explore technical approaches, propose end-to-end solutions, and implement secure interfaces and workflows for automated tool execution, data retrieval, and enhanced productivity.
Maintain and enhance the company’s platform and infrastructure using Microsoft SQL Server and Python.
Build visualization tools, analytical tests, and mathematical algorithms to provide an overview of software and IT-backed systems owned by the Data Team.
Assist IT-based technical teams in building systems to interface with third-party APIs asynchronously for data fetches.
Integrate financial and alternative datasets for research and trading using Python, agile development methodologies, and Object-Oriented Design (OOD).
Ensure the quality of pricing and reference data through manual and automated data integrity processes.
Partner with front office analysts and quantitative analysts to provide new software engineering ideas and enhancements.
Automate internal organization systems and data collection processes using SQL and No-SQL databases, and tools/frameworks like Hadoop, Spark, Redis.
Develop tools to enhance and streamline data used in client portfolio reviews utilizing User Interface (UI) development knowledge.
On-board multiple datasets from different vendors and technical sources, cleaning vendor data and normalizing it into organization’s software, IT systems, and databases.
Perform troubleshooting or code inspection actions on internal systems for company traders.
Provide adequate data search options for internal analysis tools.