---
title: "The Convergence of Data  \u0026  Software Engineering in the Age of AI"
description: "Explore how modern data teams are evolving into core engineering organizations, driven by AI and ML demands. Key parallels in architecture, security \u0026 delivery."
categories: ["trends"]
keywords: ["data engineering","software engineering","AI demands","data products","microservices","data mesh","data security","observability tools","Theory Ventures","Tomasz Tunguz"]
ai_summary: "Explore how AI is transforming data teams into core engineering organizations, enhancing collaboration and product development."
date: 2023-10-20
lastmod: 2026-07-23
canonical_url: https://www.tomtunguz.com/data-engineering/
author: "Tomasz Tunguz"
---

The patois of data teams has become a dialect of modern engineering teams because the commonalities in the stack. 

| Core Eng | Data Eng | 
| --- | ---|
| Products | Data Products | 
| Microservices | Data Mesh | 
| Service Level Agreements | Data Contracts | 
| Access Control | Data Security | 
| Observability | Data Observability | 

This convergence signals how far data teams have evolved into core
engineering teams. [Machine learning's demand for data](https://tomtunguz.com/reorientation-of-the-data-team/) has accelerated this
movement because AI needs data to function.  

Data teams receive tickets from their internal customers & develop data products that serve both internal  &  external users,  much like a classic product management  &  engineering team.

Data teams architect their systems in a modular way, paralleling the microservices movement in software design.

Data contracts express the commitments data teams make to others in the company about data freshness, format,  &  consistency - again drawing parallels to the service-level agreements in core engineering.

Security systems govern access to databases akin to secrets management  &  identity access management solutions do in the cloud.

To identify issues in production systems, both types of engineers leverage observability tools for anomaly detection  &  responding to incidents.

Twenty years ago, the data team meant managing centralized BI  &  producing analysis in Excel.

But today, data teams are engineering teams in their own right, with specialized tools for their particular domain.

They are central to product development  &  operations in technology companies. Their evolution into full-fledged engineering teams enables more seamless collaboration with software developers.