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Tech Stack

A strategic, production-tested selection of the tools, frameworks, and patterns I leverage to build reliable data platforms, secure cloud infrastructure, and deterministic AI systems.

Production AI, Agents & Applied MLOps

  • Agentic Frameworks: LangGraph, Pydantic AI, LangChain, LiteLLM.
  • Model Orchestration: Model Context Protocol (MCP), Vertex AI (Model Garden, Pipelines), Gemini, Anthropic Claude, Hugging Face, Ollama.
  • Vector Storage & Semantic Search: Qdrant, pgvector, Pinecone, Chroma.
  • Evaluation & Observability: LangSmith, Arize Phoenix, step-by-step custom tracing, semantic guardrails.

Data Engineering & Lakehouses

  • Processing Engines: Polars, DuckDB, Apache Arrow, Apache Spark (PySpark), Databricks, Pandas.
  • Modern Orchestration: Dagster, Apache Airflow (Cloud Composer / MWAA), Prefect.
  • Storage & Table Formats: Apache Iceberg, Delta Lake, Apache Parquet, Cloud Storage, Amazon S3.
  • Transformation & Modeling: dbt-core (SQL-based modular modeling), SQL, Kimball dimensional modeling, Data Vault 2.0.

Cloud & Platform Infrastructure

  • Cloud Providers: Google Cloud Platform (GCP), Amazon Web Services (AWS).
  • Infrastructure as Code (IaC): Terraform (Modular landing zones), Terragrunt, OPA Rego, Conftest (Policy-as-Code).
  • Containers & Orchestration: Docker, Kubernetes (GKE / EKS), Google Cloud Run, Amazon ECS / Fargate.
  • CI/CD & Local Toolchain: GitHub Actions, GitLab CI, Just runner, uv.

Languages, Databases & Standards

  • Programming Languages: Python, SQL, Rust, Scala, Bash.
  • Databases: PostgreSQL, DuckDB, MySQL, BigQuery, Snowflake, Redshift.
  • Quality & Engineering Standards: Data Contracts, Schema Evolution, Idempotency, Pre-commit quality gates, Conventional Commits, SemVer.