Senior Data Engineer

Dexcom

1. Analyzed and optimized data, resulting in a 20% reduction in supply chain inefficiencies and a 15% increase in sales forecast accuracy on Google Cloud Platform.
2. Utilized Google Cloud Data Studio to interact with Google Cloud SQL databases, executing diverse data tasks and ensuring seamless data flow.
3. Engineered a streamlined data ingestion state machine with Google Cloud Functions and Google Cloud SQL for pipeline efficiency, reducing processing time by 40%, using Python for custom functions.
4. Operated within an extensive technology stack including Hadoop, Google Cloud SQL, Google Cloud Storage, Python, SQL, and Git, ensuring versatility for Python-based GCP projects.
5. Utilize Apache Airflow to schedule and coordinate data tasks across various Google Cloud services.
6. Implemented Google Cloud Data flow for real-time data ingestion into GCP, enhancing availability and accuracy, with Python-based custom data transformations.
7. Configured and managed Google Cloud Pub/Sub, capturing real-time changes across tables to maintain consistency, with Python-based event processing.
8. Designed and automated Google Cloud data integration workflows using Google Cloud Composer, leading to a 30% improvement in data processing efficiency, with custom Python components.
9. Played a pivotal role in automating infrastructure provisioning on GCP GKE using Terraform, reducing deployment time by 50%, with Python-based automation scripts.
10. Demonstrated expertise in operating Google Compute Engine, Google Cloud Storage, Google Cloud SQL, and building data lakes, with Python-based data processing components.
11. Resolved complex data challenges, including GCP data security with vendors, resulting in enhanced data privacy and compliance, with Python-based encryption and decryption.
12. Participated in Agile methodologies, sprint planning, and daily Stand-ups, enhancing collaboration and iterative development with Python development for GCP solutions.
13. Conducted comprehensive GCP and Snowflake data analysis, providing crucial insights for decision-making, leveraging Python for advanced analytics.
14. Spearheaded the implementation of GCP-specific features like Google Cloud Composer and Google Cloud Functions, contributing to workflow optimization, with custom Python components.
15. Integrated with BigQuery for large-scale analytics and efficient querying, optimizing for high performance and scalability within the GCP architecture.
16. Implemented GCP infrastructure-as-code efforts using Terraform, ensuring consistent and efficient deployments, with Python-enhanced provisioning.
17. Utilized Terraform for managing GKE clusters, streamlining GCP infrastructure deployment, integrated with Python-based automation.
18. Played a key role in automating infrastructure provisioning on GCP GKE using Terraform, reducing deployment time by 50%, with Python-based automation scripts.
19. Created a Tableau dashboard to visually represent the supply chain efficiency improvements achieved through data analysis and optimization on the Google Cloud Platform.
20. Utilized line charts or trend graphs to demonstrate the 15% increase in sales forecast accuracy, providing a clear visual representation of the improvements over time.

New York Institute of Technology

Operations and Supply Chain management