Staff Software Engineer-Trading

Addepar is a global data and AI platform that empowers investment professionals to manage and advise on complex financial information. They are seeking a highly experienced Staff Software Engineer to join their Order Management System team in Trading, focusing on building a scalable trading and rebalancing platform for wealth management firms. The role involves architecting and implementing engineering solutions, mentoring team members, and collaborating with product managers and engineers to deliver impactful business outcomes.

Responsibilities:

• Architect, implement, and maintain engineering solutions to solve complex problems; write well-designed, testable code
• Lead individual project priorities, deadlines, and solutions
• Collaborate effectively with product managers, engineers, and partners on projects
• Active support of business needs during US hours
• Act as an engineering representative to the client and product support and steer communications from engineering standpoints
• Communicate technical ideas and set direction on projects with a focus on solving business challenges
• Mentor other engineers on the team
• Participate in the design and development of a strategic product for Addepar
• Write clean, efficient, and maintainable code that's also scalable and extensible

Requirements:

• B.S., or M.S. in Computer Science or similar technical field of study (or equivalent practical experience)
• 8+ years of software engineering experience
• Expert-level proficiency in backend development, with a focus on Java
• Good experience on AWS or any other cloud platform
• Experience with databases, SQL, NoSQL, OLAP, and/or data lake architectures
• A strong ownership mentality and drive to solve the most important problems
• Passion for implementing standard processes with a bias toward smart automation
• Proven ability to collaborate with and mentor other engineers
• A rapid learner with robust analytical and problem-solving abilities
• Experience in data processing and analysis using SQL, PySpark, or similar frameworks is a plus