Shaunda Cunningham

• Architected and operated a cloud-native data platform using Terraform, dbt, Fivetran, and BigQuery, supporting a 10× increase in data volume and users.
  
• Developed and productionized an LLM-based classification system (OpenAI) to analyze LinkedIn data, improving accuracy of student job-outcome reporting and enabling downstream analytics for program effectiveness.
• Implemented CI/CD workflows for data infrastructure and transformations, improving deployment reliability and reducing manual intervention.
  
• Established data governance and reliability standards (tests, contracts, monitoring) to improve trust in analytics and downstream reporting.
  
• Partnered with cross-functional teams (product, engineering, and leadership) to translate ad-hoc data needs into sustainable pipelines and dashboards, fostering a data-driven culture across the organization.

• Contributed to the re-architecture of Snowflake's role-based access control (RBAC), executing a complete overhaul through Terraform to enhance data access management.
• Spearheaded the implementation of data masking techniques for personally identifiable information (PII) in Snowflake, fortifying data privacy and compliance.
• Architected and developed a comprehensive data contract pipeline infrastructure, leveraging Lambda functions and Python-based Great Expectations for data validation.
• Pioneered the setup of a Databricks project tailored for data scientists, facilitating advanced machine learning modeling.
• Implemented monitoring and alerting systems using AWS CloudWatch, Splunk, and Datadog, ensuring proactive issue identification, debugging, triage, and resolution.

• Designed and optimized ETL workflows using Apache Airflow, leveraging Snowflake for seamless data integration and analytics, resulting in improved data processing efficiency by 30%.
• Orchestrated Docker containers on EC2, engineered CI/CD pipelines, and automated cloud infrastructure provisioning with Terraform, reducing deployment time by 50% and ensuring consistent and reliable application delivery.
• Managed AWS resources (EC2, S3, RDS, Lambda) and implemented robust data security measures, including IAM policies and encryption, ensuring the confidentiality and integrity of sensitive data.
• Collaborated with cross-functional teams, providing training on data processes and best practices, fostering a culture of data-driven decision making, and ensuring alignment across departments.

• Leveraged SQL and large-scale proprietary datasets to diagnose pricing algorithm issues, improving model accuracy and increasing revenue lift across multiple markets.
• Conducted root cause analyses on performance anomalies, using data visualization and statistical summaries to inform strategic pricing and go-to-market adjustments.

Focus on End-to-End AI Applications, including Retrieval-Augmented Generation (RAG), Fine-Tuning, Agentic AI, MLOps, and Guardrails.

7-month, full-time Backend Engineering program focused on MVC/RESTful design and Test-Driven Development using Ruby, Rails, and PostgreSQL