I design and build production-grade data systems: batch ELT with dbt + Airflow/Meltano, streaming with Kafka/Spark, analytics serving on ClickHouse and DuckDB/Polars for fast iteration. I care about data contracts, tests, lineage, cost/performance, and developer experience (pre-commit, CI, reproducibility).

• Focus: Retail analytics, event streaming, lakehouse on S3 + ClickHouse, dbt modeling, cost optimization.
• Toolbox: Python, SQL, ClickHouse, dbt, Airbyte/Meltano, Airflow, Spark, Kafka, Terraform, Docker, AWS.
• Principles: “Measure twice, cut once.” Automate quality, document decisions, ship small and observable changes.

• ETL Mobilidade — end-to-end ELT scaffold
  Python · dbt · GH Actions · Docs (MKDocs) · Tests
  ➜ https://github.com/Robso-creator/etl_mobilidade

• ELT with Meltano (ind.) — pipelines & dev-prod workflows
  Meltano · dbt · Pre-commit · CI templates
  ➜ https://github.com/Robso-creator/elt_meltano_ind

• Spark Streaming — Unstructured Data — streaming blueprint
  Spark Structured Streaming · Kafka-ready · Dockerized dev
  ➜ https://github.com/Robso-creator/spark-streaming-unstructured-data

• Discord Bot (DX demo) — testing, docs & CI discipline
  Pytest · Pre-commit · MIT License · Pages
  ➜ https://github.com/Robso-creator/discord_bot

Want a quick overview? Check my Portfolio / Case Studies with context, architecture and trade-offs: https://robsonsampaio.vercel.app.

• Languages: Python (Typer/FastAPI), SQL
• Storage/Compute: ClickHouse (MergeTree, MVs), DuckDB/Polars, S3
• Orchestration: Airflow, Meltano, dbt (core + tests)
• Streaming: Kafka, Spark Structured Streaming
• Quality & Lineage: Pytest, Pandera/Great Expectations, OpenLineage/Marquez
• Infra/DevEx: AWS, Terraform, Docker, pre-commit, GitHub Actions

• Contracts & Tests: schema validation (Pandera/GX) + Pytest (unit/integration) with coverage gates.
• CI/CD: Ruff + MyPy + Pytest on PR, Codecov badges, Dependabot for security.
• Docs: docs/ with MKDocs auto-deployed (GitHub Pages), architecture diagrams and runbooks.
• Reproducibility: make up && make seed && make test && make demo (Docker Compose).
• Observability: lineage (OpenLineage), data SLOs (freshness/completeness), cost/perf notes for ClickHouse (partitions, codecs, TTLs).
• Security: least-privilege IAM, secrets management, audit logs.

• LinkedIn: https://www.linkedin.com/in/robson-allef
• Email: robson.sampaio@rtechs.tech

Engenheiro de Dados focado em ELT/streaming, ClickHouse, dbt e Airflow, com práticas de qualidade, contratos de dados, CI e documentação. Curto construir stacks reprodutíveis, com observabilidade e custo/performance na prática.

Destaques:
etl_mobilidade · elt_meltano_ind · spark-streaming-unstructured-data · discord_bot
Portfólio com estudos de caso:

Contato: https://www.linkedin.com/in/robson-allef · robson.sampaio@rtechs.tech