Software Engineer specializing in enterprise data infrastructure, platform systems, and cloud-native architectures. Currently at AT&T, I work on production-grade data pipelines, orchestration workflows, and metadata governance systems that operate at scale across distributed cloud environments.
Modernizing enterprise metadata ingestion and governance workflows by building PySpark-based orchestration pipelines ingesting 700k+ files/day, classifying distributed data assets into a graph-based knowledge system to replace fragmented manual discovery processes.
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Designed and operationalized a unified semantic data model and ontology spanning Databricks, Snowflake, and Infoworks to standardize metadata representation and enable consistent enterprise-wide data lineage and governance.
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Developed and managed production-grade ETL infrastructure for ingestion, transformation, validation, and integrity enforcement across cloud-native Azure environments supporting enterprise analytics workloads.
Delivered production web features in collaboration with Product, Design, and Analytics teams, supporting high-traffic consumer-facing experiences on the Peacock platform.
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Refactored the playback fork screen using React component-based architecture, improving UI consistency, maintain-ability, and long-term extensibility.
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Implemented dynamic lead and marketing modules for the Olympics Hub page, supporting large-scale traffic events and content launches.
Designed and implemented Apache Airflow integration into the network database; resulted in improved data management, streamlining data pipelines from C and Perl legacy code to Python
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Created automated email notifications for task failures, ensuring timely response to issues
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Developed and deployed a Python package to interface with internal company servers, allowing for efficient retrieval and parsing of configuration files and enhancing data integration and management; successfully tested and implemented on two networks with scalability and intended to support 20+ networks in the future
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Constructed a full-stack application using Django, Chart.js, Next.js, and React.js; application interfaced with Snowflake database, displaying network configuration data and dynamic charts for 20+ internal teams
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Collaboratively developed a technician routing algorithm utilizing AI/ML concepts. Saw a near 40% improvement over currently implemented models and built a front-end to demonstrate user experience with the model for the Intern Innovation Challenge.
