MAIA WORKSHOP · PRIVATE · BY REQUEST

​Agentic Data Engineering in a day. At your office. On your data.

A private Maia Workshop puts your data engineers, analytics engineers, and the leaders who run them in a room with the Maia field engineering experts for half a day. We scope a representative workload from your environment, hand it to Maia, and watch it build a tested, documented pipeline while your engineers review the plan before each step. You leave with the pipeline, the architectural decisions written down, and an honest read on agentic data engineering for your stack.
PUBLIC · OPEN TO All
Register your place
Pick the session that works for you. Limited seats per room.
Half a day, hands-on
Working pipeline by the end
Agent plan reviewed before every step
At your office, on your data
“Maia feels like having a team of junior data engineers who never sleep.”
1 week to 6 minutes
Pipeline build timeline at Balfour Beatty before and after Maia.
Dan Adams
Global Analytics Manager
Edmund Optics
How it works

Your data, from request to production

1

Request

Tell us who you are and what you'd like to work on. Two minutes.
2

Discovery call

A 30-minute call with your Maia AE to confirm the workload, the data, and who needs to be in the room.
3

Workshop day

A 30-minute call with your Maia AE to confirm the workload, the data, and who needs to be in the room.
4

Recap and decision

Within a week, you have the pipeline, the recap, and a clear read on production. Decide on next steps — or walk away.

Why request a private workshop

Three reasons people bring Maia in-house for a day Subheadline: AI in data engineering is a scope and trust problem before it is a tooling problem. A private workshop is the fastest way to surface answers against your own stack, with your engineers reviewing the agent's work, not watching a slide.
1

See an agent build something real, on your data

Maia takes a workload you brief in advance and works through it in front of the room. Schema discovery, transformation logic, tests, documentation, lineage. Built against your warehouse, while your engineers review the plan before each step.
2

Past the live build: how the agent decides and what runs around it

After the live build, engineers go deeper. Orchestration patterns, Git workflow, RBAC, lineage trace, agent evaluation, deployment. We show the parts of agentic data engineering that don't fit on a slide: how the agent decides, where it asks for human review, what it does when a transformation fails partway through.
3

Leave with a pipeline and a position

The pipeline built in the room is yours. So is the recap covering what was scoped, what the agent did, the open questions, and what to test next in your environment. Engineers walk out with code. The data leader walks out with a business case that can survive the next budget meeting.
WHO SHOULD ATTEND

For people who build, and the people who lead

Maia Workshops are written for two readers in the same room. The engineer who will own the pipeline if it ships. The data leader who will own the budget if it scales. Both have to leave with the same picture, which is why public sessions are deliberately built for joint attendance.

No preparation needed. No data to bring. Just show up ready to build.
Who comes to private workshops
VP of Data
Head of Data Engineering
Data Engineer
Director of Data Platforms
Senior Data Platform Engineer
Analytics Engineer
Private workshops work best with four to eight people from the same organisation. Engineering and leadership in the same room.
The Agenda

Half a day. Hands-on from the jump.

The structure is the same in both customer sessions. The workload is a Matillion ETL job. Snowflake or Databricks as the target, depending on where you are heading. Convert Workloads runs in the room on a wider sample so you leave with real numbers, not estimates.
Request a private workshop
15 mins

Welcome & setup

Get your environment ready and meet the team
15 - 20 mins

Scene-setting

Use case overview – what we're solving for today
90 mins
Key Session

Live session

Maia builds against your workload while your engineers review the agent plan. Schema discovery, transformation logic, tests, documentation, lineage, orchestration, deployment.
15 - 20 mins

Wrap-up

Walk through the output, the open questions, what to do next in your stack.
WHAT YOU WALK AWAY WITH

You don't leave with slides.

The pipeline built in the session is yours: code, tests, documentation, lineage. Every attendee also receives an AI-generated recap covering what was scoped, what the agent did, where it asked for human review, and where it would go next. Worth handing to a manager or a CFO.
Plus some cool goodies. (You'll see.)

Pick a date. Bring an engineer

Sessions run frequently, by region. Bring two to four people from the same organization if you can: engineering and leadership in the same room. The day works better that way.
Register for a session
120,000+ hours
Hours of manual data engineering effort saved
Up to 100x
Faster data delivery and throughput
$25M+
In productivity value unlocked