Data Architect

A large investment firm is seeking a hands-on technical Senior Data Engineer and Architect to build and own a scalable analytics and dashboard platform that tracks deal performance across private credit and specialty finance asset classes. This person will partner closely with leadership, members of the investment team, and broader firm wide technology team to define requirements, build data pipelines and metrics for large data sets, and deliver a web-based portal where dashboards and analytical tools are centrally maintained. The role also includes an opportunity to lead pragmatic AI initiatives and elevate best practices in modern analytics and engineering.

This role will require not only the technical skills to build such a platform, but also a deep understanding of finance, risk analytics, credit, loans, and structured and unstructured investment data.

Responsibilities:

• Design, build, and maintain a suite of dashboards that track deal/asset performance, risk, and key portfolio KPIs (e.g., collateral performance, delinquency, prepayment, loss metrics, triggers/covenants, concentrations, vintage curves).
• Build a unified web portal where dashboards, reports, and self-serve analytics tools are organized, versioned, and accessible with appropriate permissions.
• Act as point of contact for third party data providers to help normalize and validate deal-level data.
• Support ad-hoc analysis for investment memos, portfolio reviews, and ongoing surveillance.
• Own project plans and delivery cadence: scope, milestones, dependencies, and stakeholder updates.
• Liaise with broader technology team to ensure solutions meet firm standards.
• Identify and champion high-impact AI opportunities for future growth and technological advancement.

Required Qualifications

• 10 years of relevant experience as a full-stack engineer in asset-backed finance, private credit, or an adjacent buy-side setting.
• Advanced Python skills for data engineering and analytics (pandas/numpy, API integration, scripting, testing).
• Strong SQL skills and experience building analytics-ready data models with large data sets and hands-on Snowflake experience
• Experience building dashboards and/or data applications (e.g., Streamlit/Dash, Plotly, Power BI/Tableau, or equivalent) with attention to UX for investment professionals.
• Experience translating ambiguous needs into finalized products, managing stakeholders, and delivering on timelines.
• Strong communication skills with the ability to work directly with investors and explain technical concepts clearly.

Core Technical Stack

• Languages: Python, SQL, React
• Infrastructure: Redhat Openshift, Containers
• Data Warehouse: Snowflake, Microsoft SQL Server
• Visualization / Apps: Streamlit/Dash/Plotly, Tableau
• Version Control & Delivery: Git, Microsoft Azure DevOps