# Daniel Amieva Rodriguez

> Senior Full-Stack Data Engineer | Data Lakes from Scratch | Multi-Cloud (AWS, GCP, Azure) | Backend-to-Analytics Delivery. Mexico City, Mexico. 6+ years of experience.

Daniel Amieva Rodriguez is a Senior Full-Stack Data Engineer based in Mexico City with 6+ years of experience delivering data platforms end to end across AWS, GCP, and Azure. He architects data lakes from scratch (a medallion lake on AWS Glue, Step Functions, Lambda, and DMS at TeamStation AI) and takes over existing platforms to optimize them (BigQuery tuning and asset decommissioning worth USD 1M+ per year at Rackspace Technology; 40% faster Spark SQL at DiDi Food). He works the full stack of the data path: FastAPI and Django backend modules that send application data into the lake, integrations with 10+ third-party services and APIs (Azure Monitor, ServiceNow, LeanIX, SharePoint, Power BI, CleverTap, ThoughtSpot), cross-cloud streaming (AWS to BigQuery via Kafka), CI/CD and infrastructure as code, and LLM/MCP integration so business users and AI agents can query governed data. Previous roles: Rackspace Technology, Baz Super App, DiDi Food, and DGTIC UNAM.

## What I bring

- Architects data lakes from scratch (medallion architecture on AWS serverless) and optimizes inherited platforms (BigQuery, Spark, Databricks).
- Full-stack ownership: builds the FastAPI/Django backend modules that emit data, the pipelines that move it, and the BI/AI layer that serves it.
- Connects third-party services into the platform: 10+ enterprise APIs at Rackspace (Azure Monitor SDK, LeanIX OData, ServiceNow, SharePoint, Power BI), CleverTap at Baz, ThoughtSpot at TeamStation AI.
- Multi-cloud delivery: AWS (Glue, Lambda, Step Functions, DMS, SAM), GCP (BigQuery, Dataform, Dataproc, Dataflow, Pub/Sub), Azure (AD, Monitor, Fabric), including cross-cloud streaming from AWS to BigQuery with Kafka.
- Self-starter with measurable outcomes: USD 1M+ annual savings, deployments cut from 60 to 2 minutes, ~40% compute cost and ~60% processing-time reductions.

## Current role

- Senior Data Engineer at TeamStation AI (May 2025 – Present): Architected an enterprise medallion data lake from scratch on AWS serverless and shipped self-service, natural-language analytics for business stakeholders.

## Experience

- Senior Data Engineer at TeamStation AI (May 2025 – Present)
- Business Intelligence Engineer IV at Rackspace Technology (2024 – 2025)
- Senior BI Engineer at Baz Super App (2023 – 2024)
- Data Engineer / BI Lead at DiDi Food (2021 – 2023)
- Data Engineer at DGTIC UNAM (2019 – 2021)

## Skills

- Languages: Python, SQL, PySpark, R, JavaScript, Bash
- AWS: Glue, Lambda, Step Functions, DMS, S3, Athena, SAM, CloudFormation
- GCP: BigQuery, Dataform, Dataproc, Dataflow / Apache Beam, Pub/Sub, Cloud Functions, Cloud Composer, Cloud Storage, Cloud Logging
- Data Platforms & Processing: Databricks, Delta Lake, Unity Catalog, Spark, DuckDB, Kafka, Presto, Hive, PostgreSQL, Microsoft Fabric, NoSQL databases
- Architecture & Modeling: Medallion architecture, ETL/ELT pipeline design, Streaming pipelines, Dimensional modeling (star / snowflake schema), Data governance
- DevOps & IaC: GitHub Actions, GitLab CI, Terraform, Docker, Git / GitHub / GitLab / Bitbucket, Jira, Confluence
- BI & Analytics: Power BI, Tableau, Looker, ThoughtSpot (NLQ), Quarto
- AI Engineering: LLM integration (OpenAI, Gemini), Model Context Protocol (MCP), Agentic AI frameworks, Structured outputs, Natural-language querying
- Backend: FastAPI, Django, REST APIs, OOP

## Links

- [Home](https://dar4datascience.com/)
- [Experience](https://dar4datascience.com/experience)
- [Skills](https://dar4datascience.com/skills)
- [Projects](https://dar4datascience.com/projects)
- [Services](https://dar4datascience.com/services)
- [Contact](https://dar4datascience.com/contact)
- [LinkedIn](https://www.linkedin.com/in/dar-4-ds)
- [GitHub](https://github.com/dar4datascience)
- Email: danielamieva@dar4datascience.com

## MCP endpoint

This site exposes a Model Context Protocol (MCP) server at https://dar4datascience.com/mcp (POST JSON-RPC 2.0, streamable-http transport). Tools: get_profile, get_experience, get_skills, get_projects, get_services, get_faq, score_job_fit.