PAM Data Solutions Developer

Overview

Join a dynamic, business-integrated team that delivers high-impact analytics and automation solutions. In this role you’ll design and optimize data pipelines, build dashboards, and support advanced analytics initiatives that directly enhance decision-making. This role offers autonomy, rapid project execution, and exposure to machine learning, all within a highly collaborative environment that values innovation and efficiency. Direct Business Impact:
Work closely with portfolio managers, advisors, and operations teams to deliver solutions that matter. Agility & Autonomy:
Enjoy the speed and flexibility of a small, empowered team backed by strong firm resources. Innovation:
Leverage cutting-edge tools and explore ML/AI applications in financial services.

• Develop, maintain, and optimize ETL processes and data pipelines for critical dashboards and reports.
• Ensure data integrity, quality, and governance across multiple systems.
• Build and maintain reporting solutions using SQL Server, SSRS, and Power BI.
• Deliver accurate, timely insights for advisors, portfolio managers, and operations teams.
• Support ML Operations initiatives; learn and apply techniques using tools like scikit-learn and PyTorch.
• Collaborate on AI-driven portfolio allocation and product advisory projects.
• Document processes, maintain version control, and contribute to team knowledge-sharing.
• Continuously explore new technologies to improve automation and scalability.

• Must be able to obtain the SIE, Series 7, and Series 66 licenses within 12 months of hire.
• Bachelor’s degree in Computer Science, Information Systems, Finance, or a related field (or equivalent professional experience).
• Strong stakeholder management and project prioritization capabilities.
• Strong analytical, problem-solving, and troubleshooting skills.
• Excellent communication skills and the ability to translate technical work into business value.
• Highly coachable, proactive, and motivated to learn.
• Proficiency in SQL (SQL Server preferred) with demonstrated experience in building ETL processes, preferred.
• Experience with Python, including Pandas and SQL Alchemy, preferred.
• Familiarity with Power BI and SSRS reporting solutions, preferred.
• Exposure to ML tools and techniques, particularly in financial data context, preferred.
• Experience working in financial services, asset management, or related industries, preferred.