I'm a Senior Data & AI Engineer who builds the systems that make enterprise data actually usable pipelines, lakehouses, and now the agentic AI layer that sits on top of them. Five years in, I've worked across the full stack of modern data engineering - cloud platforms, dimensional modeling, large-scale PySpark, orchestration, and most recently AI agents and retrieval systems. I care about the unglamorous parts: clean grain, sane contracts, fast queries, pipelines that don't wake people up at 3am. I also care about the new parts — how LLMs, agents, and protocols like MCP are changing what a data platform is for. Currently at Bristol Myers Squibb, leading the data and AI layers of an internal intelligence platform. Always up to talk shop on data, AI, or anything in between. SkillSet: Programming: Python, SQL, PySpark, Scala Cloud — AWS: S3, Glue, Lambda, Athena, Redshift, SQS, SNS, EventBridge, AppFlow, DataZone, Secrets Manager, Lake Formation, EKS, RDS Aurora DB, Step Functions, CodeBuild, Kinesis Firehose, EC2, DynamoDB, EMR, OpenSearch, Bedrock Cloud — Azure: Databricks, Azure Data Factory (ADF), Synapse, Azure Data Lake Storage (ADLS Gen2) Lakehouse, Warehousing & Analytics Engineering: Snowflake, Apache Iceberg, Delta Lake, Iceberg UniForm, ClickHouse, Redshift, PostgreSQL, SAP HANA, Databricks Serverless SQL Warehouse, Photon, dbt-core (Glue and Databricks adapters), Unity Catalog, Delta Live Tables, Kedro, Impala, Hive, MySQL, NoSQL, BigQuery, Data Marts, Data Lake, Glue Studio Data Modeling: Kimball Dimensional Modeling, Star Schema, Snowflake Schema, SCD Types 1/2/3, Medallion (Bronze/Silver/Gold), Data Vault, Fact and Dimension Design, Semantic Layers Orchestration & CI/CD: Apache Airflow, Dagster, AWS Step Functions, Databricks Workflows, Databricks Asset Bundles, Control-M, GitHub Actions, Jenkins, AWS CodeBuild, EventBridge AI / GenAI: LangGraph, LangChain, Model Context Protocol (MCP), A2A Protocol, AWS Bedrock, Amazon Titan Embeddings, pgvector, RAG, Hybrid BM25 + Vector Search, NL-to-SQL, SQLGlot, AWS OpenSearch, NLP, Regex, NER Big Data & Processing: Apache Spark, PySpark, Hadoop, Hive, ETL, Batch Processing, Big Data, Performance Tuning DevOps & Observability: Grafana, Langfuse, Kubernetes, Docker, Git BI & Visualization: Power BI, Tableau, Excel, Matplotlib Fundamentals: Data Structures and Algorithms, OOP, System Design, Problem Solving, Data Warehousing, ETL Pipelines, Agentic AI Systems, Multi-Agent Orchestration