What is a DBRE? The Database Reliability Engineering Role Explained

For a long time, databases were different. While the rest of infrastructure moved to DevOps, then to SRE, then to platform engineering, database operations followed its own path. DBAs became some of the most versatile people in any engineering organisation: part architect, part performance analyst, part capacity planner, part crisis responder. They designed schemas, planned migrations, tuned queries, and kept production running. The scope of the role kept growing, but the tooling and practices around it didn't keep pace.

The Database Reliability Engineer is what happens when you apply the principles of Site Reliability Engineering to that gap. It's not a rebranding of the DBA role. It's a complementary discipline that emerged to address a specific set of challenges at scale.

Where the term came from

Google created the first Site Reliability Engineering team in 2003, led by Ben Treynor Sloss. The insight was that running production systems at scale required a hybrid of software engineering and operations, not one or the other. Google published the Site Reliability Engineering book in 2016, and the SRE model spread rapidly across the industry.

But databases were slower to adopt the model. Even as companies built SRE practices for their application infrastructure, database operations continued to rely on dedicated specialists whose deep expertise was difficult to codify, share, or scale. The best DBAs were doing extraordinary work, but much of that knowledge lived in their heads rather than in automation.

In 2017, Laine Campbell and Charity Majors published Database Reliability Engineering through O'Reilly, coining the term that gave the emerging discipline a name. Their argument was that databases deserved the same engineering rigour that SRE had brought to the rest of infrastructure. Not because DBAs weren't doing valuable work, but because the operational burden was preventing them from doing their best work: the architecture, the capacity strategy, the performance analysis that only experienced practitioners can do well.

Charity Majors was simultaneously building Honeycomb and helping define the modern observability movement. That connection between database reliability and observability wasn't coincidental. It's core to what the DBRE role is about.

What a DBRE actually does

The DBRE role exists at companies like GitLab, Wise, Revolut, Cloudflare, and Okta. While the specific responsibilities vary, the core pattern is consistent across all of them.

A DBRE automates operational toil. Google's SRE book defines toil as work that is manual, repetitive, automatable, and devoid of enduring value. For databases, that means everything from provisioning new instances to running standard health checks to performing routine maintenance. The DBRE's job is to turn those into automated processes so that human attention can go where it matters.

A DBRE builds fleet-wide consistency. A DBA typically has deep knowledge of how each server should be configured. A DBRE takes that same expertise and encodes it into systems that maintain consistency across the entire fleet. When you're running dozens or hundreds of database instances, that kind of codified knowledge becomes essential.

A DBRE owns incident response for database issues. They're on the on-call rotation, they run the post-mortems, and they build the runbooks that make the next incident faster to resolve. Critically, they also build the tooling that reduces the need for human intervention over time.

A DBRE creates developer-facing self-service tooling. DBAs often end up as a bottleneck for schema changes, not because they want to be, but because the organisation has no other safety mechanism. The DBRE builds the guardrails and review processes that let developers move safely, freeing the DBA from routine approvals so they can focus on the changes that actually need expert judgement.

DBRE vs DBA: complementary, not competing

The distinction between a DBA and a DBRE isn't about seniority or capability. Most experienced DBAs already do strategic work: migration planning, architecture reviews, capacity forecasting, vendor evaluation. The challenge is that operational demands constantly pull them away from it. A DBRE discipline creates the automation and tooling layer that reduces that operational pull, letting DBAs spend more time on the high-value work they're already capable of.

The DBRE role is fully inclusive of a DBA's responsibilities, but extends into engineering territory. In practice, the two roles make each other better: the DBA brings the deep domain knowledge that no amount of automation can replace, and the DBRE builds the systems that amplify that knowledge across the organisation.

Why the role matters now

Three forces are making the DBRE role more critical than it was even five years ago.

Database estates are growing. The average engineering organisation now runs dozens to hundreds of database instances across PostgreSQL, MySQL, and increasingly specialised engines. Even the best DBA team can't give individual attention to every instance at that scale. The DBRE model extends their reach by codifying expert knowledge into automation that works across the entire fleet.

Downtime costs are escalating. Recent industry surveys suggest that for most mid-size and large organisations, a single hour of database downtime often exceeds $300,000, and many enterprises report figures north of $1 million. The DBRE's focus on automation, observability, and proactive capacity management directly reduces the frequency and severity of these incidents.

The talent gap is widening. Senior DBREs command $150K–$200K+ in the US, with roles at Okta requiring 4+ years of PostgreSQL experience at scale. These people are rare and expensive. Every organisation that needs database reliability is competing for the same limited pool of experienced practitioners. There simply aren't enough DBREs to go around.

What companies are looking for in a DBRE

Looking across DBRE job descriptions from GitLab, Wise, Okta, Cloudflare, and others, the common requirements cluster around a few themes. Deep expertise in PostgreSQL or MySQL is table stakes, as these are the engines where the role is most prevalent. Experience with cloud-managed databases (Aurora, Cloud SQL, Azure Database) is expected. But beyond the technical foundations, what distinguishes the DBRE from the DBA is the engineering perspective: experience building automation, writing tooling, and thinking in systems rather than servers.

GitLab's DBRE team, for example, works on PostgreSQL cluster management, automation pipelines, capacity planning, and query performance review, all oriented toward fleet-level reliability. Wise describes their DBREs as a blend of database engineering, DevOps, and software development. The role sits at the intersection of all three.

The future of the DBRE

The trajectory of the DBRE role mirrors what happened with SRE: as the discipline matures, more of the repetitive investigative and diagnostic work gets automated, freeing human practitioners for higher-leverage work like architecture decisions, capacity strategy, and incident prevention.

This is exactly the space where autonomous tooling becomes valuable. Not as a replacement for the DBRE or DBA, but as a way to give a small team the capacity of a much larger one. When the level-1 and level-2 investigation work is handled automatically, practitioners can focus on the strategic work that requires human judgement: migration planning, architecture reviews, and the kind of deep analysis that comes from understanding both the database engine and the business context.

The DBRE role isn't going away. If anything, the combination of growing database estates, escalating downtime costs, and a persistent talent shortage means more organisations will need the discipline that DBREs bring. The question is whether they'll have enough human practitioners to meet the need, or whether they'll need to find ways to augment their existing team's capacity.