Klaudia Pietrzyk

• Designed and maintained scalable serverless backend services on Google Cloud Platform using Cloud Run and Cloud Functions.

• Developed secure REST APIs implementing authentication and authorization mechanisms (JWT/OAuth2, RBAC).

• Optimized Cloud Run deployments, reducing infrastructure costs while improving application performance and scalability.

• Collaborated with cross-functional teams to build internal tooling supporting content production pipelines.

• Managed cloud infrastructure using Terraform and automated deployments across DEV, STAGING, and PROD environments.

• Led the development of scalable ETL pipelines using Airflow and DBT for a luxury brand analytics platform.
• Implemented High-Availability (HA) architectures on GCP and AWS, ensuring 24/7 reliability for critical data processing workloads.
• Optimized cloud infrastructure for performance, cost efficiency, and scalability.

• Tech Leading in a Machine Learning squad, mentoring a team of engineers and enforcing SOLID principles.
• Led the technical design of AI data pipelines processing 10M+ records weekly, ensuring seamless integration between ML models and backend services
• Engineered complex data transformation logic using custom decorators and context managers to ensure system modularity and extensibility.
• Designed and implemented robust data pipelines that processed and analyzed 10M+ marketing data records weekly.
• Collaborated with product managers and stakeholders to align technical solutions with business metrics, improving time-to-insight by 30%.

Developed a cloud-native data processing platform for large-scale mobile device usage analytics.

• Built data ingestion and validation pipelines collecting and processing high-volume mobile device datasets.
• Integrated pipelines with BigQuery data warehouse enabling high-performance analytical queries.
• Implemented data integrity validation mechanisms to ensure accuracy and consistency across ingestion stages.
• Automated infrastructure provisioning and deployments using Terraform and containerized workloads.

Environment: Python, Flask, GCP, BigQuery, Terraform, Docker, Kubernetes, Redis

Worked on backend systems for financial data processing and analytics.

• Designed services to collect and process stock market data including price feeds, trading volumes, and financial indicators.
• Implemented pipelines for storing and validating financial datasets.
• Developed neural-network based models to analyze market patterns and trends.

Supported development of interactive 3D applications using Unity and C#.

• Implemented UI/UX elements and gameplay mechanics based on design specifications.
• Conducted functional testing and debugging of game prototypes across platforms.