GCP Developer Resume Example

Senior GCP Data & MLOps Engineer · Altair Data Solutions

Seattle, WA · 2023 - Present

• Architected and implemented a serverless data processing pipeline on GCP using Dataflow and BigQuery, reducing data latency by 40% and processing costs by 25% for real-time analytics.
• Developed and deployed MLOps workflows using Vertex AI Pipelines and Kubeflow, automating model training and deployment for 3 critical machine learning models, improving deployment frequency by 3x.
• Led the migration of on-premise data warehouses to BigQuery, handling over 50TB of historical data and optimizing query performance, resulting in a 30% speed improvement for complex analytical queries.
• Implemented robust data governance and security measures for sensitive data in BigQuery and Cloud Storage, achieving 100% compliance with internal data privacy policies.
• Mentored junior engineers on GCP best practices, BigQuery optimization, and MLOps principles, enhancing team productivity by 15%.

GCP Data Engineer · NexGen Analytics

Seattle, WA · 2020 - 2022

• Designed and built scalable data ingestion systems using Cloud Pub/Sub and Dataflow, processing over 1TB of streaming data daily with 99.9% uptime.
• Optimized BigQuery datasets and queries for a key reporting dashboard, decreasing report generation time by 35% and improving user experience for 500+ daily users.
• Collaborated with data scientists to provision and manage GCP resources (VMs, Cloud Storage) for ML model training, reducing setup time for new experiments by 50%.
• Automated daily ETL processes using Cloud Composer (Apache Airflow), improving data freshness and reducing manual intervention by 80%.

B.S. in Computer Science · University of Washington

Seattle, WA · 2016 - 2020

• Graduated Magna Cum Laude with a GPA of 3.8/4.0.
• Relevant Coursework: Distributed Systems, Machine Learning, Database Management, Data Structures & Algorithms, Cloud Computing.
• Capstone Project: Developed a scalable data ingestion system for real-time analytics, demonstrating proficiency in data streaming and processing technologies.

GCP Developer · Cloud Harbor Technologies

Austin, TX · 2023 - Present

• Developed and deployed scalable microservices using Python and Go on Google Kubernetes Engine (GKE), reducing deployment times by 30% and improving service reliability by 25%.
• Designed and implemented CI/CD pipelines with Cloud Build and Argo CD, automating infrastructure provisioning and application deployments for over 15 critical services.
• Optimized GCP resource utilization across multiple projects, leading to a 15% reduction in monthly cloud spending through BigQuery cost controls and appropriate GCE instance sizing.
• Managed and monitored production environments using Cloud Monitoring and Logging, proactively identifying and resolving issues to maintain 99.9% uptime for core applications.
• Collaborated with security teams to ensure compliance and implement best practices for identity and access management (IAM) and network security on GCP.

Data Engineer · DataStream Analytics

Dallas, TX · 2020 - 2022

• Designed and built robust ETL pipelines using Apache Beam and Dataflow to process over 10TB of daily customer data, improving data availability for analytics by 40%.
• Managed and optimized BigQuery datasets, implementing partitioning and clustering strategies that reduced query costs by 20% and improved query performance by 35%.
• Developed custom Python scripts and Airflow DAGs for data ingestion, transformation, and loading, ensuring data quality and consistency across multiple data sources.
• Collaborated with data scientists to provision and manage machine learning infrastructure on AI Platform, reducing model training time by 10%.

Master of Science in Computer Science · University of Texas at Austin

Austin, TX · 2018 - 2020

• GPA: 3.8/4.0
• Thesis: 'Optimizing Real-time Data Pipelines on Distributed Systems'
• Relevant Coursework: Cloud Computing Architectures, Distributed Systems, Machine Learning Engineering