embedded analytics , change data capture , Apis, Data Modeling, Permissions, query engines, lakehouse-style storage, safe action execution, in-process analytics, serving layers, extensibility, modern data architectures, DuckDB, natural-language querying, source systems, event streams, Text-to-SQL evaluation, data ingestion, SDKs, observability, downstream activation, AI products, developer platforms, data platforms, querying, analytics products, AI-native data experiences, data quality governance, infrastructure products

graph databases , BigQuery, Schema Design, Data Modeling, Sql, Data Quality, Dataproc, data pipelines, JSON-LD, API-first development, entity resolution frameworks, data engineering concepts, Knowledge Graphs, ontologies, Observability, Monitoring

Data AI and GenAI landscape and enterprise adoption patterns, Supporting pursuits and shaping proposals, Leading complex consulting engagements, Working alongside engineering and architecture teams

Enterprise Architecture, Data Analytics, Cloud Platforms, Modern Engineering, Ai

Machine Learning, Cnn, Clustering, Deep Learning, Nlp, MLops, Artificial Neural Networks, Decision Trees, Azure, Python, AWS, LSTM, Support Vector Machines, YOLO, Quadratic Programming, genetic algorithms, Large Language Models

data engineering , snowflake , Power Bi, Pyspark, AWS Glue, Informatica, Google Cloud, Azure ML, Databricks, Azure, AWS, SI application development, Business intelligence, Azure Foundry, GCP BigQuery

data engineering , Ml, Cybersecurity, Data Governance, Azure, AWS, Enterprise Integration Architectures, Industry 4.0 frameworks, PLCs, Ai, Digital Twin technologies, Data Historians, Dcs, Industrial Data Platforms, Industrial Communication Standards, SCADA