I’m Alex Kargin, a Senior Data and Analytics Engineer based in Boca Raton, Florida. I have built and supported production data systems since 2013—currently as a contract Data Engineer at Silicon Army, previously at Restaurant Brands International / Burger King and, before that, nearly six years at Orangetheory Fitness.
A recurring thread through that work is migration and modernization. At Orangetheory I led the move from Aurora and Redshift to Snowflake—source-system analysis, schema and data mapping, transformation logic, cleansing, reconciliation, validation, and cutover. Earlier database engineering roles covered migrations across MySQL, PostgreSQL, SQL Server, and Aurora, along with query tuning, OLTP-to-OLAP modeling, and production support through DEV/SIT/UAT/Production release workflows.
I build data solutions end to end—from raw operational data and complicated business rules to trusted Snowflake models, Power BI dashboards, APIs, and production AI applications.
A lot of that modeling is what the industry now calls the semantic layer: defining metrics and business logic once, in the warehouse, so dashboards, applications, and AI agents all read the same numbers instead of each re-deriving them from raw source systems. It is the same dimensional modeling and dbt work I have been doing for years, pointed at a new consumer—something I wrote about recently after dbt Labs reported cutting AI token costs ~98% by feeding agents modeled summaries rather than raw source data.
My experience combines data engineering, analytics engineering, business intelligence, and applied AI. I work across Snowflake, dbt, Dagster, Airflow, Power BI, Python, SQL, AWS, Azure, PostgreSQL, ClickHouse, FastAPI, and Next.js.
I have delivered analytics solutions supporting Finance, Accounting, Operations, Marketing, forecasting, and executive reporting. My work includes dimensional modeling, semantic models, DAX, KPI development, data-quality validation, cloud migrations, performance optimization, governance, and production support.
I also build practical AI systems, including document intelligence, RAG, vector search, NLP, computer vision, and private LLM applications. My focus is not AI for demonstration purposes—it is using the right technology to solve a real business problem reliably, securely, and cost-effectively.
