Data Engineer with experience in analytics engineering, quantitative risk analysis, and performance attribution across financial services and investment reporting. Skilled in Python, SQL, Power BI, Azure, Snowflake, Data…
Data Engineer with experience in analytics engineering, quantitative risk analysis, and performance attribution across financial services and investment reporting. Skilled in Python, SQL, Power BI, Azure, Snowflake, Databricks, and automation tools, with experience building dashboards, ETL pipelines, and reporting workflows.
<p>Designed and developed the front-end for Terminus, an AI-powered freight security product, building a Power BI interface to deliver insights to stakeholders from analysts to senior executives.<br>
Engineered a scalable analytics pipeline using Microsoft Fabric, Snowflake, and SharePoint, applying advanced data modeling and DAX to build an optimized semantic model.<br>
Developed an automated Power BI Report Usage and Cost Metrics tracker to support governance and monitor operational costs associated with the Terminus platform.</p>
<p>Developed and maintained cloud infrastructure and ETL pipelines for investment and financial reporting using Azure Data Factory, Databricks, Python, and SQL, improving data processing efficiency by 30%.<br>
Automated infrastructure provisioning and data transformations using Terraform, Azure DevOps, and dbt, improving deployment consistency and reducing CI/CD errors by 25%.</p>
<p>Supported investment analytics across fixed income mandates, performing performance attribution and analyzing key risk and return drivers.<br>
Built a Python and Dagster-based reconciliation framework to compare P&L drivers across FactSet and Fund Accounting, improving analytics validation and issue resolution.<br>
Automated monthly attribution into a one-click workflow, using GitHub Copilot to accelerate development and improve operational efficiency.</p>
<p>Engineered 10+ Power BI dashboards integrating on-premises databases and Snowflake via semantic models and DAX optimization, improving reporting performance across millions of rows for 10+ stakeholders.<br>
Built automated refresh and validation workflows using Power Automate, while establishing version control and custom VEGA visualizations through GitHub to improve reliability and development efficiency.</p>
<p>Produced daily and monthly performance, attribution, and exposure analytics across Total Fund and asset classes including Private Equity and Real Estate.<br>
Leveraged SQL and Power BI to analyze portfolio performance, risk, exposures, and compliance data while performing reconciliation and resolving reporting discrepancies for Investment Finance & Risk stakeholders.</p>
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