Senior Application Engineer

We are seeking a highly skilled Senior Application Engineer with deep T-SQL expertise to join the Liquid Credit Engineering Team, a key division within our broader Investment Systems organization. In this role, you will focus on designing, developing, and supporting the critical technology solutions that power our liquid credit investment workflows—spanning trade processing, portfolio reporting, and advanced data management.

You will collaborate closely with portfolio managers, traders, operations professionals, and fellow engineering teams to build, optimize, and scale high-performance systems that support the firm's core investment functions.

Req# 1060032160

Responsibilities

• Solution Development: Design, develop, and maintain robust, scalable software solutions supporting complex liquid credit investment processes and workflows
• Data Integration: Seamlessly integrate high-volume financial data across multiple systems involved in credit investing to ensure a unified and accurate data landscape
• Database Optimization: Write and optimize complex stored procedures, queries, and data models in SQL Server (2016 or later) to ensure maximum database performance and data integrity
• Reporting Solutions: Build, customize, and enhance reporting capabilities using SQL Server Reporting Services (SSRS) and SQL-based data models
• Collaboration & Alignment: Work in lockstep with cross-functional teams, including front-office users (traders, portfolio managers), operations teams, and product stakeholders
• Architecture & Best Practices: Participate in system architecture design sessions and contribute actively to engineering standards, documentation, and best practices
• Production Support: Troubleshoot and resolve critical production issues in a timely manner to maintain system reliability and minimize business impact

Requirements

• T-SQL Expertise: Strong hands-on experience with SQL Server (2016 or later), featuring advanced skills in query optimization, data modeling, and writing complex stored procedures
• Reporting Tools: Proven track record of building and enhancing reports using SSRS
• Software Engineering Fundamentals: Solid understanding of modern software engineering principles, including data structures, Object-Oriented Programming (OOP), and system design
• Financial Services Context: Experience working in financial services, asset management, or investment systems (highly preferred)
• Execution & Analytical Skills: High attention to detail, excellent analytical and problem-solving abilities, and the capacity to manage multiple priorities in a fast-paced environment
• Communication: Outstanding verbal and written communication skills, with the ability to translate complex technical concepts to non-technical business stakeholders

Nice to have

• Programming Languages: Proficiency in Python for data processing, scripting, or backend development
• Industry Systems: Hands-on experience with Allvue's cloud-native platform (Everest), particularly with trade/order management modules
• Domain Knowledge: Strong understanding of the trade lifecycle, Order Management Systems (OMS), or Portfolio Management Systems (PMS)
• Cloud Infrastructure: Familiarity with AWS (cloud services, architecture, and deployment)
• Modern DevOps: Experience with CI/CD pipelines, DevOps practices, and microservices architecture

An artificial intelligence system is software that is developed with one or more techniques that can, for a given set of human-defined objectives, using algorithmic information processing, generate outputs such as content, predictions, recommendations, or decisions with varying levels of autonomy (“AI”). Tasks that humans have traditionally done by thinking and reasoning are increasingly being done by, or with the help of, AI to help create efficiencies.EPAM may use AI during the recruitment process, in connection with collecting or processing your personal data. Some (non-exhaustive) examples of tasks that EPAM may use AI for include conducting initial screening, creating transcripts of interviews, and assessing applications/CVs against defined job description criteria to make suggestions to the individuals evaluating your candidacy.Your personal data and the results of any processing are not shared with AI applications outside of EPAM infrastructure. While EPAM may use AI to help create efficiencies during the recruitment process, EPAM does not use AI to make hiring decisions, which is done by EPAM Talent Acquisition and management.