The Future Of Data Engineering - The Powers of Agentic Development

OFFERINGS:

Agentic Data Engineering
MCP & Context Engineering

Agentic Data Engineering
MCP & Context Engineering

Framework-Driven Development
Production-Ready Pipelines

Framework-Driven Development
Production-Ready Pipelines

AGENTIC DEVELOPMENT

Your data engineers are too expensive to write boilerplate..

Every hour spent on scaffolding, config, and repetitive transformation patterns is an hour not spent on what actually moves the business.

What if an AI agent could ship production-ready pipelines?

Your data engineers are too expensive to write boilerplate..

Every hour spent on scaffolding, config, and repetitive transformation patterns is an hour not spent on what actually moves the business.

What if an AI agent could ship production-ready pipelines?

WHY

Your team builds the pipelines. Not the business.

Data engineers spend most of their time on work that doesn't require their expertise. Scaffolding, YAML config, transformation boilerplate, naming conventions. The same patterns, project after project.

The real value: getting trusted data in front of decision-makers fast enough to actually inform those decisions. This gets squeezed into whatever time is left.

The tooling exists to change that. Not just copilots that autocomplete a line of SQL. Agents that reason.

Your team builds the pipelines. Not the business.

Data engineers spend most of their time on work that doesn't require their expertise. Scaffolding, YAML config, transformation boilerplate, naming conventions. The same patterns, project after project.

The real value: getting trusted data in front of decision-makers fast enough to actually inform those decisions. This gets squeezed into whatever time is left.

The tooling exists to change that. Not just copilots that autocomplete a line of SQL. Agents that reason.

IN BRIEF

Why:

Your most expensive people spend their days on your least valuable work. Pipeline scaffolding, config files, boilerplate transformations, naming conventions.

It's necessary, but it doesn't move the needle. Meanwhile, the work that actually creates value waits - business logic and getting insights to decision-makers.

What:

An agentic AI layer that understands your full platform context. Not autocomplete. An agent that knows your medallion architecture, your naming conventions, your transformation patterns, and your deployment pipeline.

It writes the right code, in the right place, following your conventions with appropriate data quality precautions.
 
Production-ready pipelines in days, not weeks.

How:

A standardised repo structure, a layered data platform framework, and Claude-powered skills connected through MCP.

The agent reasons over your full stack because it has the context to do so. Same principle as all our AI work. The difference between a demo and production is context engineering.

Your repo, your conventions, your platform. We help you wire it up.

what we know:

1.

Copilots autocomplete. Agents reason.


The difference is context. When the agent knows your architecture, your conventions, and your deployment pipeline, it stops guessing and starts engineering.

That's not prompt magic. That's context engineering.

The right repo structure, the right metadata, the right skills, all wired up so the agent has everything it needs before it writes a single line.

2.

Structure compounds.


Every convention you encode makes the next pipeline faster to build, easier to maintain, and harder to get wrong.


New team members productive on day one because the framework encodes your standards, and the agent teaches them as they go.

When you take framework-driven development seriously, the tooling follows naturally.

3.

This isn't a product. It's a way of working.


Your repo. Your conventions. Your platform. Supercharged with agentic development that compounds over time.

Every skill you add makes the next pipeline faster and frees up more time for the work that actually creates value.

We can help you set it up. Your team takes it from there.

contact us

Curious how AI fits into your data stack? Let's talk.

Wondering where to start with AI? We probably asked the same questions. We've tested AI across data platforms, analytics, and architecture with real clients, on real data. If you're exploring where AI fits in your organisation, we're happy to share what we've learned.

No pitch, no commitment, just a conversation.

Wondering where to start with AI? We probably asked the same questions. We've tested AI across data platforms, analytics, and architecture with real clients, on real data. If you're exploring where AI fits in your organisation, we're happy to share what we've learned.

No pitch, no commitment, just a conversation.

Christian Gert

Partner

cgh@backstagecph.dk

Christian Gert

Partner

cgh@backstagecph.dk

Mads Buhl

Partner

mb@backstagecph.dk

Mads Buhl

Partner

mb@backstagecph.dk

Julius Bech

Partner

jb@backstagecph.dk

Julius Bech

Partner

jb@backstagecph.dk

client cases

Client cases we are proudly showcasing

Backstage ApS

Hejrevej 34B TV

2400 København NV

+45 61 95 67 40

Backstage ApS

Hejrevej 34B TV

2400 København NV

+45 61 95 67 40

Backstage ApS

Hejrevej 34B TV

2400 København NV

+45 61 95 67 40