Python · SQL · PySpark · Apache Spark · AWS Glue · Airflow · Databricks · Snowflake · Redshift · AWS Bedrock
6+ years engineering and operating production cloud data platforms across financial services and healthcare, including governed data services that support analytics, machine learning, and generative AI. I specialize in secure ETL/ELT pipelines, AI/ML-ready datasets, modern data platforms, data quality, and reliable cloud infrastructure using Python, SQL, PySpark, AWS Glue, Airflow, Databricks, Snowflake, Redshift, AWS, and Azure.
I build secure, governed cloud data platforms that power analytics, machine learning, generative AI, and regulatory reporting.
At Fifth Third Bank, I engineer regulated ingestion pipelines, curated analytics layers, and governed feature and document datasets for AWS Bedrock-backed risk and compliance workflows. At CVS Health, I developed Azure Data Factory and Databricks pipelines that delivered validated healthcare claims data to analytics and ML consumers.
My strength is at the intersection of data engineering, AI-ready data delivery, and platform reliability: I design pipelines, data models, validation controls, governed datasets, cloud infrastructure, CI/CD, observability, and security as one integrated production system.
Core data and platform engineering capabilities applied across regulated financial services and healthcare environments.
Production ETL and ELT pipelines using Python, SQL, PySpark, AWS Glue, Apache Airflow, Azure Data Factory, and Apache Spark for analytics and reporting.
Cloud data warehouses and lakehouse platforms across Snowflake, Redshift, Databricks, and Azure Data Factory, with performance tuning and cost optimization.
Embedded validation, reconciliation, exception handling, retries, alerts, dependency controls, and production monitoring into data workflows to protect reporting SLAs.
Infrastructure automation and deployment reliability using Terraform, Kubernetes, Docker, Helm, GitHub Actions, Jenkins, Azure DevOps, and ArgoCD.
Security controls for regulated data using IAM, RBAC, KMS, Key Vault, Secrets Manager, private networking, encryption, and audit logging aligned with PCI-DSS, HIPAA, and SOC2.
Governed feature and document datasets for AWS Bedrock, Databricks ML feature engineering pipelines, SageMaker inference support, model-serving data workflows, and AI/ML workload observability.
Four roles across 6+ years, spanning cloud data engineering, analytics platforms, infrastructure automation, and production support.
I engineer and operate the bank's Enterprise Cloud Data Platform Modernization, building regulated ingestion pipelines, curated analytics layers, reliable orchestration, secure cloud infrastructure, and production observability for treasury, compliance, reporting, and AI-enabled workflows.
I engineered Azure Data Factory and Databricks pipelines for healthcare claims ingestion, actuarial reporting, fraud detection, and utilization prediction, combining PySpark transformations, SQL validation, Snowflake administration, Terraform automation, and HIPAA-aligned security controls.
Supported enterprise data integration and AWS migration workloads through cloud provisioning, Spark batch processing, SQL transformations, Terraform automation, Jenkins delivery pipelines, Docker containerization, and production support.
My data engineering roots — where I learned what financial close cycles really mean for the people running batch jobs at 2am. SQL performance, Python ETL patterns, and production support discipline that now informs every data pipeline I build at the infrastructure level.
Depth ratings reflect daily production use, not tutorials or side projects.
Certifications supporting my work across AWS, Azure, infrastructure as code, and generative AI data platforms.
I'm open to Senior Cloud Data Platform Engineer, Senior Data Engineer, Data Platform Engineer, Cloud Data Engineer, and AI/ML Data Platform roles — especially in regulated industries where data quality, security, and reliability are mission-critical.
Remote, hybrid, or onsite — open to relocation. Based in the San Francisco Bay Area.
Open to Senior Cloud Data Platform Engineer, Senior Data Engineer, Data Platform Engineer, and Cloud Data Engineer roles. I bring hands-on experience across banking and healthcare data platforms, cloud infrastructure, compliance, and production reliability.