Role: Elastic architect • Elastic SME

Overview: Joined a rapidly expanding Enterprise Observability group as Elastic Architect and SME. Implemented auditing procedures and architectural and indexing optimizations that improved performance and lowered operating costs by 30% across a portfolio of Elastic Cloud environments.

Key Outcomes:

• Implemented paradigm changes in indexing strategy and lifecycle management to reduce platform cost by 30%.
• Introduced platform auditing capabilities across the stack and used that to identify opportunities to increase performance.
• Established Observability Workshop program to mentor users and identify opportunities for query performance improvements.

Role: Elastic engineer & SME • solution design • data engineer • data analyst

Overview: Took ownership of early-stage Elastic Cloud deployments and evolved into a mature observability platform to support development teams and business services.

Key Outcomes:

• Ingested logs, metrics, and APM traces to enable availability, troubleshooting, and analytics dashboards.
• Implemented alerting to route incidents to the right teams faster.
• Standardized patterns for data onboarding and dashboard usage across teams.

Role: MSSQL and NoSQL data modeling and schema design • DBA • Elastic engineer & SME • data analyst

Overview: Designed and implemented an enterprise search solution built on self-hosted Elasticsearch clusters, consolidating data from disparate sources to provide enterprise search capability to internal and external audiences.

Key Outcomes:

• Installed and tuned architecture, indexing, and caching strategies to optimize operational costs and provide query capabilities across the organization.
• Established and optimized MSSQL data assets and SSIS pipelines to integrate source data.
• Maintained, upgraded, and optimized the Elastic clusters over six years.
• Designed and delivered solutions across Elasticsearch, Logstash, Kibana, Beats agents and custom tooling for business and analysis solutions alongside a software engineering team.

Role: Observability engineer • solution design • data engineer • data analyst

Overview: Designed and implemented a self-hosted Elastic-based observability platform that unified Windows server monitoring with application and database log analysis, providing a single source of operational insight; collaborated with developers and business owners to showcase new data-driven capabilities and train teams to apply them in daily operations.

Key Outcomes:

• Introduced observability practice to software development and business teams.
• Delivered monitoring and research capabilities with $0 budget increase.
• Implemented Elastic Observability pillar with agent-based collection using Elastic Beats and custom Logstash pipelines.
• Delivered Kibana dashboards for operations, troubleshooting, and trend analysis.
• Built pipelines and dashboards to surface performance signals and streamline troubleshooting.

Role: Solution design • data engineer • data analyst

Overview: Part of a team that designed, built, and maintained a business-focused data warehouse platformed on Microsoft SQLServer that unified data from disparate systems to enable business analysis, streamline application integrations, and deliver consistent, trusted datasets across the organization.

Key Outcomes:

• Deployed Elastic beat agents to collect hardware and system metrics
• Deployed data pipelines using SSIS and custom tooling to collect business data from line-of-business applications.
• Leveraged the consolidated and standardized data schema to facilitate integrations between applications and vendors.
• Solution design guidance and data access patterns that are maintainable and supportable.

Role: Creator • mentor • tutor • solution designer • data analyst

Overview: Created and led an ongoing program to improve organizational data literacy and analysis skills through structured mentoring, targeted training sessions, and individualized hands-on support for analysts and business teams.

The program began organically from troubleshooting requests and grew into a cross-division community of practice.

Key Outcomes:

• Identified individuals with data aptitude across the organization to participate.
• Offered a range of topics including basic SQL coaching, query support, data literacy fundamentals, advanced Excel, PowerBI, and Kibana
• Mentoring in business analysis support to clarify stakeholder questions before building solutions.
• ETL/data engineering to source from enterprise apps and provision end-user data marts.