I lead a team of infrastructure and software engineers who are building a state of the art data integration and sharing platform on AWS. We focus on the automated enablement of Enterprise Data Access, cross domain Integration and data virtualization.

General Responsibilities:- Primary contributor to modernization of State Farm's Enterprise Data Architecture and Legacy Data Warehouse, to a modern cloud based data ecosystem using principles of Data Mesh and Hybrid architecture supporting Distributed Storage, Data Virtualization, Centralized Consumption and Governance.- Expense management and oversight over multi-million dollar budget including labor, software licensing, offsite/offshore labor costs, and cloud based expenditures- Performed General HR duties as well as general career mentoring for direct reports- Implementation and enforcement of Continuous Integration/Continuous Deployment (CI/CD), Infrastructure as Code (IaC), and Agile Development practices- Acted as Relationship Manager for vendor procured software, including upfront risk evaluation, purchasing, contract renewals, support contracts, and feature requestsAccomplishments:- Built automated data governance solutions to minimize time to market while increasing auditability of data.- Built out of over 30 database clusters using Infrastructure as Code (IaC) (Terraform), storing multiple Petabytes of data in support of a variety of general BI/Data Science, and operationally used analytical data. This service included a variety of solutions including Redshift, S3, Aurora, DynamoDB, and Neo4j- Focus on efficient use of cloud resources to optimize cost- Implemented full multi-region Disaster Recovery plans- Built out both centralized and decentralized storage in support of Data Mesh principles- Supported the development of a centralized Data Catalog- Implemented Data Sharing/Data Mesh across several AWS accounts to minimize data movement, maximize data availability, and isolation of workloads.- Implemented advanced monitoring and alerting to ensure high availability and protection against bad actors and processes.- Provided support for ~300 legacy databases, primarily hosted on the zOS/DB2 Mainframe platform

- Leadership of a team of Big Data Solution Architects that consulted with a large variety of use cases, primarily focused on the adoption of Hadoop. The primary goal of this team was to enable our business partners that were currently leveraging our legacy data warehouse to modernize and start leveraging Hadoop technology allowing for the retirement of our older systems, and also enable new technology that was better suited for large scale Data Science model development.- Heavily involved in enabling all governance activities for the Hadoop environment. Some of the key issues were: - Handling of all types of sensitive data, and providing a security framework to enable a least privileged access model - Properly cataloging data to identify its sensitivity as well as prevent duplicity and unnecessary storage costs. Provided oversight of the overall architecture related to moving on premise analytical datastores and warehouse to the AWS Cloud. I led a team of solution architects who performed the following items. - Design of Data Lake architecture - Partnered with business to evaluate and select and enable cloud hosted governance tooling to provide capabilities for Data Cataloging, Data Quality, Data Lineage, and Governance (EDC, IDQ, and Axon). - Partnered with multiple high profile multi-petabyte modernization/migration efforts for our Claims and Property and Casualty business areas. - Implementation Statistical Models developed by our Data Science team into the AWS Cloud (SageMaker). This includes the development of the data pipelines both in and out of the engine, building and deploying all AWS components needed to run the model .

- Enablement of Data Science organization’s infrastructure and tooling. - Installation/Maintenance of tooling, servers, GPU Appliances etc - Hosting of Reporting/Dashboard software - Partnered with Data Governance Organization to understand and optimize the process of approving and allowing for the movement and use of data for analytical purposes. The primary objective being to greatly shorten the duration of time to market for Data Science Model Development/Deployment, while adhering to strict data governance practices and government oversight.

Team Lead setting guidance and patterns for Enterprise Data Architecture. - Enterprise Canonical Modeling- Canonical Message Modeling- Guidance for non-standard data modeling such as key/value stores- SQL Reviews and Tooling

- Consulted on a variety of performance related issues with Staples.com- Provided detailed plan for scalability during peak traffic hours on Black Friday/Cyber Monday- Deployed Splunk and AppDynamics for use in detailed application monitoring

- Provided guidance for a team of performance analysts to perform detailed performance testing and subsequent tuning of J2EE applications.- Perform Capacity Management for J2EE Servers/Applications- Deep dive troubleshooting and analysis of J2EE applications, including Heap Analysis- Setup/rollout of Performance monitoring tooling, including Splunk, HP Diagnostics, and AppDynamics

Aviation Electronics Technician, specialized in maintenance and repair of fire control radar systems for the Grumman F-14 Tomcat