Architected across-cloud data integration layer leveraging Azure Data Factory and Databricks to consolidate gameplay, chat, and engagement telemetry into unified analytics pipelines supporting real-time decision systems. Developed scalable Python ETL frameworks using Azure Functions, Synapse Pipelines, and PostgreSQL to automate ingestion of user interaction data and enable conversational reporting dashboards for product teams. Optimized multi-tenant data lake structures on Azure Data Lake Gen2, introducing Delta format and partitioning strategies that improved query efficiency and reduced storage costs by 35 percent. Designed secure API endpoints with FastAPI and Azure API Management to deliver high-availability access to processed analytics data for AI and ML workloads. Implemented CI/CD automation via Azure DevOps, orchestrating infrastructure provisioning, testing, and deployment for data pipelines and validation scripts. Integrated ML workflows with Azure Databricks MLflow trackin

Senior Data Engineer at Circle

September 30, 2024 - September 30, 2024

Led migration of financial data pipelines from AWS Glue to Azure Data Factory and Synapse Analytics, achieving higher orchestration reliability and tighter integration with the enterprise data lake. Developed automated ETL pipelines with Python, Databricks (Spark SQL and PySpark), and PostgreSQL to support blockchain transaction analytics and machine-learning risk-scoring models. Implemented data validation frameworks using Great Expectations and integrated quality checks into ADF pipelines to ensure consistency across multiple data sources. Designed and deployed CI/CD pipelines using Azure DevOps and Terraform to manage infrastructure as code and promote versioned releases of data processing workflows. Built APIs using Flask and FastAPI to deliver real-time compliance metrics and AI-generated insights through web dashboards consumed by global finance teams. Optimized query performance in Synapse Analytics with partitioned views, caching strategies, and adaptive query plans, reducing e

Data Engineer at Facebook

November 1, 2021 - November 1, 2021

Engineered distributed data pipelines processing billions of user events daily using Spark, Hive, and Presto, forming the foundation for advertising analytics and conversational AI features. Built data transformations and aggregation layers in Python and SQL to support NLP training datasets powering chat-based recommendation systems. Designed modular Airflow DAGs with dynamic task generation and dependency management, improving throughput and observability for ML data feeds. Optimized data models and schemas in Hive and Presto to reduce query latency and enable real-time reporting across ad-performance and user engagement analytics. Partnered with machine learning and research teams to build feature engineering pipelines for voice assistant and messenger conversational AI projects. Developed data quality monitors using custom Python scripts and SQL assertions that validated billions of records daily to maintain consistency across multiple clusters. Contributed to internal tooling enhan

Data Analyst at Wells Fargo

February 28, 2017 - February 28, 2017

Developed ETL processes using SQL Server Integration Services (SSIS) and Python to aggregate financial transaction and risk data into a centralized analytics warehouse. Designed PostgreSQL and SQL Server data models to support regulatory reporting and operational dashboards for risk management and compliance teams. Optimized complex SQL queries and indexing strategies, reducing execution time for key reporting jobs by over 50 percent. Automated data validation and reconciliation checks through Python scripts and scheduled batch processes, improving accuracy and timeliness of daily reports. Created interactive visual dashboards in Power BI and Tableau for executive reporting, integrating data from financial systems and third-party APIs. Partnered with IT and security teams to establish role-based data access controls and encryption standards to protect sensitive customer information. Supported initial cloud migration initiatives by testing data transfer and validation workflows to Azure