AI Data Engineering Bootcamp
18 weeks to build and run the data behind AI: the data engineering core that job posts ask for, verified coding agents, a semantic layer, MCP, and documents turned into AI-ready data.
An 18-week bootcamp for people who already write SQL and Python and want to be the data engineer who builds and runs the data behind AI. You learn the core that job posts filter on (ingestion, modeling, quality, orchestration, Spark and streaming) and, every week, how to work with coding agents and verify what they produce. You prepare data for agents to consume, with a semantic layer and MCP, and turn unstructured documents into AI-ready data. The whole project thread uses open data from Wikipedia and Wikidata about Mexico's municipalities. You finish with three portfolio projects documented in English, ready for interviews with and without AI.
Next cohort
Coming soon
Investment
Curriculum
What you'll learn
Three six-week phases. In every topic you work by hand first and then with a coding agent, verifying what it produces. Each phase ends with a portfolio project.
Phase 1: Foundations with an agent beside you
Weeks 1-6Phase 2: A governed, agent-ready platform
Weeks 7-12Phase 3: Scale, unstructured data and operations
Weeks 13-18Who it's for
Is this bootcamp for you?
It is built for people who already have a technical base and want to specialize in data for AI. It is not a from-scratch course.
Data or BI analyst
You know SQL and want to move from querying data to building the systems that produce it, now for AI too.
Backend developer
You already code and want to specialize in data: pipelines, modeling and the data agents consume.
DevOps or platform engineer
You run infrastructure and want to add orchestration, data quality and an AI-ready platform.
SQL Bootcamp graduate
You finished the SQL foundations at NIEVA and are looking for the next step on the path.
What's included
Everything you get
What you take with you during and after the 18 weeks.
Live sessions every week
18 sessions with Mike, with room for questions and code review.
Three portfolio projects
Two integration projects and a capstone, on public GitHub and documented in English.
- Verified batch ELT pipeline
- Governed, agent-ready platform
- Capstone: data for people and agents, with MCP
Coding agents every week
Every topic by hand first and then with an agent, verifying what it produces with data and tests.
Interview preparation
Interview lessons with and without AI, an English resume and spoken mock interviews in English.
Cloud electives
Optional: take your capstone to AWS (recommended), Snowflake or Azure.
Private cohort community
A private channel to work through questions with the rest of your cohort.
One year of platform access
The materials stay available for a year after the bootcamp ends.
Tools
Stack
The core runs on your machine with Docker or on free plans that don't ask for a card. For the coding agent there is a free route to get started; for the whole bootcamp a paid agent or an API key is the better choice. The cloud electives use free trials that do ask for a card, and we tell you before you start.
dbt Core + MetricFlow
Tested transformations and a semantic layer that defines each metric once, for BI and for agents.
dlt
Ingestion with incremental loading
Apache Airflow 3
Orchestration, including LLM steps
DuckDB
Local analytics
BigQuery Sandbox
Cloud warehouse, no card
PostgreSQL + pgvector
Relational database and vectors
PySpark + Databricks
Distributed processing
Apache Iceberg + Lance
Lakehouse with open tables
Redpanda + Debezium
Streaming and CDC
Docling + Presidio
Documents and PII
Ollama
Small local models for embeddings
MCP
Data for agents, securely
Soda + Elementary
Quality and observability
OpenLineage
End-to-end lineage
Docker
Reproducible environments
Investment
Choose how to enroll
Limited spots. Reserve your place with one click.
Regular price
The next cohort doesn't have a date yet. Leave your email and we'll let you know as soon as it opens.
Instructors
Meet your instructor
Learn from professionals with real industry experience.
Mike Nieva
I've worked with multiple companies and startups in professional web development and agentic architecture implementations. Technology instructor with 10 years of experience.
15-day money-back guarantee
If you're not satisfied within the first 15 days after the bootcamp starts, we refund 100% of your money. No questions, no complications.
Our commitment: We want you to be confident this investment will change your career. If for any reason it doesn't meet your expectations, get in touch and we process your full refund.
Ecosystems included
Bootcamp ecosystems and courses
Full access to the ecosystems and all their courses.
Data Engineering Ecosystem
FAQ
Everything you need to know
What do I need to know before I start?
Intermediate SQL (SELECT, JOINs, aggregations, subqueries), basic Python (variables, functions, loops, data structures), basic Git and comfort with the terminal. This is not a from-scratch bootcamp: it is built for people moving over from analytics, BI or backend. If you need the basics, NIEVA's SQL Bootcamp and Python Mini-Bootcamp are the direct preparation.
What is AI Data Engineering?
It is data engineering with everything AI added to the job: working with coding agents and verifying what they produce, preparing data for agents to consume (semantic layer, documentation and MCP), and turning unstructured documents into AI-ready data. Job posts still call the role Data Engineer; here you prepare for the one that already works with AI.
Is this Data Science, Machine Learning or AI Engineering?
No. We don't train models or build the RAG or agent app: that is the AI Engineering Bootcamp. Here you build and run the data that app consumes: reliable, governed, fresh and served.
How much will the stack cost me?
The core runs on your machine with Docker or on free plans with no card (BigQuery Sandbox, Databricks Free Edition). For the coding agent there is a free route to get started, but for the 18 weeks a paid agent or an API key is the better choice. The cloud electives (AWS, Snowflake, Azure) are optional and use free trials that ask for a card.
What computer do I need?
A laptop that runs Docker. To use small local models, 16 GB of RAM or more is recommended; if your machine falls short, there is an API key route.
Does it prepare me for interviews?
Yes. There are interview lessons with and without AI, an English resume and spoken mock interviews in English. All three projects are documented in English, as remote job posts ask.
How many hours a week do I need?
Beyond the weekly live session, budget practice time during the week. The pipeline is built incrementally: each week adds a piece to that phase's project.
When does it start?
This cohort doesn't have a date yet. Leave your email on this page and you'll be among the first to hear the start date and the launch price.
What do I take away at the end?
Three public GitHub projects documented in English, including a data platform with its own MCP server, the judgment to run data for people and agents in production, and a natural next step into the AI Engineering Bootcamp.
This cohort doesn't have a date yet
AI Data Engineering Bootcamp
Leave your email and we'll tell you the moment enrolment opens, with the start date and the launch price.
$979 USD