Jan 2026 – Mar 2026 · 2 mos · Dallas, TX · Remote

• Engineered and deployed LLM applications using Vertex AI, FastAPI, Docker, and CI/CD pipelines on GCP.
• Built RAG systems with Vector Databases (Chroma DB) and implemented semantic search using embedding
• models.
• Developed agentic AI workflows with LangChain and LangGraph for multi-step, autonomous systems.
• Applied MLOps best practices including model versioning, environment promotion, and cloud service
• integration (Cloud Run, IAM).
• Built type-safe full-stack applications with TypeScript, React, and scalable API architecture.

Apr 2025 – Jul 2025 · 3 mos

• Owned the stability and governance of Dataiku workflows across QA and production, supporting
• compliant deployment of analytics models in a regulated environment for 20+ AI/Analytics users.
• Drove 40+ Dataiku workflows to improve scheduling and reduce failures, automating ingestion and transformation; implemented changes in Python, SQL, and REST APIs; reduced average workflow runtime by 30% and cut compute costs by 20%. Authored SIQ documentation for validation and compliance, cutting audit review time by 25% and reducing onboarding time for new users from 4 weeks to 2 weeks.

May 2024 – Mar 2025 · 10 mos

• Architected and owned mission-critical ETL pipelines processing 10–20 TB/day across AWS (EMR, Glue, S3), Snowflake, and GCP, maintaining 99.9% uptime while serving financial analytics for thousands of users.
• Optimized Spark/Polars jobs to reduce end-to-end processing time by 40% and migrated from legacy Spark to Polars with zero data drift.

Apr 2024 – May 2024 · 1 mo

• Owned integration of industrial control systems into Ignition to automate hardware operations and workflows across 15+ devices.
• Built real-time dashboards and connected OT data to cloud-based reporting, improving monitoring and operational visibility.
• Reduced manual checks by 70%, enabling faster detection of equipment issues and safer pipeline operations.

Mar 2023 – Apr 2024 · 1 yr 1 mo

• Designed high-volume data migration pipelines (5–8 TB per run) and AWS cloud infrastructure (S3 → RDS/Redshift) using Spark, Glue, and Lambda.
• Automated deployments with Terraform and Concourse, enabling multiple weekly releases with near-zero rollback risk and 50% faster deployment times.

Nov 2022 – Feb 2023 · 3 mos

• Led data validation for cross-system GCP pipelines supporting inventory and supply chain analytics, ensuring reliability for 50+ analysts and reducing manual QA time by 10 hours/week.
• Developed 80+ automated test cases in Python and SQL, building workflows to validate message synchronization between distributed upstream systems; reduced average job runtime by 25% and cut compute costs by 15%.
• Achieved 95% test success rate, prevented repeated P1 data quality incidents, and increased confidence in supply chain dashboards, saving the analytics team 8 hours/week in manual validation.

Jul 2022 – Nov 2022 · 4 mos

• Owned validation and defect analysis for device feature sets across 200 iOS/macOS devices, ensuring comprehensive coverage and accuracy while reducing average QA cycle time by 30% per release.
• Designed test suites, reproduced issues across multiple OS versions, and performed detailed root-cause analysis, cutting manual QA effort by 15 hours/week and improving device stability.
• Ensured 99% feature accuracy and reduced device downtime by 75%; defect reports contributed to stability improvements shipped to tens of millions of users worldwide.

Apr 2022 – Sep 2025 · 3 yrs 5 mos

• Delivered scalable data, cloud, and backend solutions for Fortune 500 clients across finance, healthcare, and energy industries. Specialized in building high-performance ETL pipelines, cloud-native architectures, and data-driven automation using AWS, Spark, Python, Terraform, and Airflow.
• Key Projects & Achievements:
• AbbVie: Managed and optimized Dataiku pipelines across QA and production; automated ingestion via Python, SQL, and REST APIs, improving deployment efficiency by 25%. Authored qualification documentation and onboarded new users for compliance.
• Capital One: Engineered distributed Spark + Polars ETL pipelines on AWS Glue, EMR, and S3, cutting transformation time by 40% and maintaining 99.9% uptime. Automated data validation using Airflow, PyTest, and SQL for cross-engine consistency.
• Duke Energy: Built serverless ETL APIs using Lambda, Glue, and API Gateway to migrate data across S3, Redshift, and RDS. Automated CI/CD with Terraform and Concourse, improving release reliability and scalability.
• Macy’s: Created 80+ functional test cases in Python + SQL to validate GCP data pipelines, achieving 95% validation accuracy for real-time message sync.
• Western Midstream: Integrated operational hardware data into cloud dashboards using Ignition and AWS, enhancing monitoring efficiency.
• Apple: Tested and validated Apple software across 200+ devices, ensuring 99% feature accuracy and reducing downtime by 75% through effective root cause analysis and rapid issue resolution.
• Core Skills: Python, PySpark, AWS (Glue, Redshift, Lambda, EMR, S3), SQL, Terraform, Airflow, Jenkins, CI/CD, Kafka, Dataiku, GCP, REST API, ETL, Big Data, Cloud Infrastructure, Data Modeling, Automation

Jan 2022 – Feb 2022 · 1 mo · New York City · Remote

• Owned development of frontend features and backend APIs for enterprise applications, ensuring smooth integration across systems.
• Built React UI components and optimized Node.js APIs, improving data exchange and overall application responsiveness.
• Reduced page load times, increased API performance, and improved system reliability for enterprise users through targeted optimizations.

Oct 2020 – Jan 2022 · 1 yr 3 mos · Frisco, TX

• Re-engineered 230+ production ETL workflows at HCL Technologies using Python, Spark, and SQL, leveraging parameterized patterns and automation; cut runtime by 50% and improved reliability for banking applications serving thousands of daily users. Delivered workflow patterns adopted as the engineering team standard.
• Provided technical guidance and mentoring to junior engineers on ETL best practices and Spark optimization; collaborated across 3 teams to standardize workflow templates, ensuring consistent data quality and maintainability.

Nov 2018 – Aug 2020 · 1 yr 9 mos · United States

• Owned development of internal analytics tools used across multiple business units, serving as the primary engineer for core data workflows used by 150+ users across 10+ teams.
• Built New Product Studio with C, ASP.NET, and SQL to automate product data processes, and developed Titan, a visualization tool adopted by 10+ teams; reduced turnaround time for analysis from 3 hours to 30 minutes per request, cutting reporting cycle time by 83% and accelerating time to launch new products.
• Reduced manual data entry by 40% and improved operational response time by 30%; tools became the central analytics interface for multiple departments, supporting faster decision-making.

Jun 2017 – Jul 2017 · 1 mo · Richardson, Texas, United States

• Improved students’ SAT math and reading scores by 100 points through data-driven lesson planning and progress tracking.
• Led and managed a class of 30 students, applying analytical and communication skills to support academic and behavioral development.
• Ensured a safe and structured learning environment by implementing effective risk-mitigation and supervision practices.

Jan 2016 – Jan 2017 · 1 yr · Richardson, Texas, United States

• Improved student performance by 25% through data-driven lesson planning and individualized instruction focused on problem-solving and analytical reasoning.
• Applied logical thinking and quantitative analysis to simplify complex STEM concepts, enhancing student understanding and retention.
• Delivered 1-on-1 and group tutoring sessions, leveraging communication, mentorship, and feedback systems to track learning metrics and optimize outcomes.