Interviews/Quality & Security/Database Administrator (DBA)

Hire DBAs
who actually keep the database honest

With EasyEnv we build a fit test for the role. Use it to cut the noise at the top of the funnel, or to go deep on the candidates who matter.

You can even evaluate how this person works with AI. So you hire the engineer who can ship, not the one who looks good in a slide.

PostgreSQLMySQLReplicationpgbenchLive or take-home

Request a Demo Create a Free Account

Real Linux VM

Not a sandbox

systemd, kernel, full toolchain

Browser-based

Zero install for candidates

One link and they are in

Auto-graded

Pass / fail checks per challenge

Plus the full session replay

A great DBA treats the database as a system, not a black box. They know the difference between a missing index and a query that should not exist. EasyEnv hands the candidate a real database, a slow query and a replica that is falling behind.

Inside a live interview

What you see when they work.

Real database, real lag, every keystroke recorded.

billing-api

AMS

Billing-api

src

billing.py

auth.py

models.py

tests

test_billing.pyM

test_auth.py

pyproject.toml

README.md

Pybilling.py

from decimal import Decimal

def calculate_total(items: list[dict]) -> Decimal:

# Sum line totals using Decimal for currency precision

total = Decimal("0")

for item in items:

total += Decimal(str(item["price"])) * item["qty"]

return total

candidate@db-workspace:~

alice@dev:~/billing-api$

● mainPython 3.12

Claude · ready

Claude

You

Refactor calculate_total to use Decimal for currency math, and add a test.

Claude

Ask Claude...

Mike

Sam

How it works

Three steps. Zero infra to maintain.

Pick the fit test

Use a ready-made challenge or ask us to build one for your stack. Live, take-home, or both.

Send one link

The candidate clicks. A full Linux workspace boots in their browser. No installs, no VPN, no zoom-share.

Review at 2x

Replay the session, read the auto-graded checks, and decide. Most reviews take under five minutes.

The problem

Why hiring a Database Administrator (DBA) is hard.

DBAs span tuning, ops and design. CVs blur all three.

Replication and backup work is rare day-to-day, critical when it counts. The interview has to test for it.

Slow queries are an analysis skill. Whiteboards skip the plan.

Postgres and MySQL diverge in subtle ways. The candidate has to know which.

The fit test

What we measure for a Database Administrator (DBA).

Every area runs inside a real production-like workspace. The candidate works in a browser, the session records itself.

Slow query analysis

A query that runs in 12 seconds. They read EXPLAIN ANALYZE before they propose.

Index design

A workload that wants the wrong index. They explain the right one.

Replication health

A replica falling behind. They diagnose lag without restarting anything.

Backup and restore

A point-in-time recovery drill on a sandbox cluster.

CLI fluency

psql, mysql, pg_dump, mysqldump. They use them, not the GUI.

AI collaboration

Allow AI for SQL and grade whether they ran EXPLAIN on what came back.

The stack we put in front of them.

Real tools, pre-installed, accessible from the workspace terminal.

PostgreSQLMySQLMariaDBTimescaleDBPgBouncerProxySQLPatroniOrchestratorpgbenchsysbenchpg_stat_statementspt-toolkitWAL

Sample challenges

What a Database Administrator (DBA) interview looks like.

Pick from our library or ask us to build a challenge for your stack. Each one is a real workspace, not a snippet.

Challenge 01

The replica that fell behind

Scenario

A streaming replica that lagged 90 seconds an hour ago. Logs, pg_stat_replication and disk metrics are open.

What you learn

Whether they suspect WAL volume before they touch the replica config.

In the workspace

$ ls challenges/

workspace, runbook.md, README.md

candidate has:

· a real Linux box in the browser
· kubectl, docker, terraform, jq, yq
· cluster, repo and cloud creds pre-wired
· auto-checks running in the background

interviewer sees:

· every keystroke + every command
· terminal + screen recording
· auto-graded pass/fail per check

AI in the loop

Score the engineer, and how they work with AI.

AI writes SQL fast and reasons about plans slowly. EasyEnv records prompts so you see whether the candidate read EXPLAIN against the LLM-suggested query before they decided to ship it.

Allow or block AI per question, not per interview

Full prompt and response history replayed in the review

Score "verifies AI output" as a separate signal

Ready to hire a Database Administrator (DBA) who ships?

Set up your first interview in under an hour. We will help you build a fit test for this role on your stack.

Request a Demo Create a Free Account

Role FAQ

Hiring a Database Administrator (DBA), answered.

Yes. MySQL, MariaDB, PostgreSQL and TimescaleDB are all available, with seeded data and a replica.

Yes. A WAL archive and base backup are pre-staged for PITR exercises.

No. The workspace runs in their browser. Terminal, editor, ports and dashboards are all served from the EasyEnv workspace, so candidate setup is zero.

Each challenge has automated checks (did the service come back, did the test pass, did the right log message appear) plus a recording your team can replay. Most reviews take under five minutes.

Yes. AI access is a per-interview setting. Block it for fundamentals, then allow it later in the loop to assess AI collaboration separately.

Interviews/Quality & Security/Database Administrator (DBA)

Hire DBAs
who actually keep the database honest

With EasyEnv we build a fit test for the role. Use it to cut the noise at the top of the funnel, or to go deep on the candidates who matter.

You can even evaluate how this person works with AI. So you hire the engineer who can ship, not the one who looks good in a slide.

PostgreSQLMySQLReplicationpgbenchLive or take-home

Request a Demo Create a Free Account

Real Linux VM

Not a sandbox

systemd, kernel, full toolchain

Browser-based

Zero install for candidates

One link and they are in

Auto-graded

Pass / fail checks per challenge

Plus the full session replay

Inside a live interview

What you see when they work.

Real database, real lag, every keystroke recorded.

billing-api

AMS

Billing-api

src

billing.py

auth.py

models.py

tests

test_billing.pyM

test_auth.py

pyproject.toml

README.md

Pybilling.py

from decimal import Decimal

def calculate_total(items: list[dict]) -> Decimal:

# Sum line totals using Decimal for currency precision

total = Decimal("0")

for item in items:

total += Decimal(str(item["price"])) * item["qty"]

return total

candidate@db-workspace:~

alice@dev:~/billing-api$

● mainPython 3.12

Claude · ready

Claude

You

Refactor calculate_total to use Decimal for currency math, and add a test.

Claude

Ask Claude...

Mike

Sam

How it works

Three steps. Zero infra to maintain.

Pick the fit test

Use a ready-made challenge or ask us to build one for your stack. Live, take-home, or both.

Send one link

The candidate clicks. A full Linux workspace boots in their browser. No installs, no VPN, no zoom-share.

Review at 2x

Replay the session, read the auto-graded checks, and decide. Most reviews take under five minutes.

The problem

Why hiring a Database Administrator (DBA) is hard.

DBAs span tuning, ops and design. CVs blur all three.

Replication and backup work is rare day-to-day, critical when it counts. The interview has to test for it.

Slow queries are an analysis skill. Whiteboards skip the plan.

Postgres and MySQL diverge in subtle ways. The candidate has to know which.

The fit test

What we measure for a Database Administrator (DBA).

Every area runs inside a real production-like workspace. The candidate works in a browser, the session records itself.

Slow query analysis

A query that runs in 12 seconds. They read EXPLAIN ANALYZE before they propose.

Index design

A workload that wants the wrong index. They explain the right one.

Replication health

A replica falling behind. They diagnose lag without restarting anything.

Backup and restore

A point-in-time recovery drill on a sandbox cluster.

CLI fluency

psql, mysql, pg_dump, mysqldump. They use them, not the GUI.

AI collaboration

Allow AI for SQL and grade whether they ran EXPLAIN on what came back.

The stack we put in front of them.

Real tools, pre-installed, accessible from the workspace terminal.

PostgreSQLMySQLMariaDBTimescaleDBPgBouncerProxySQLPatroniOrchestratorpgbenchsysbenchpg_stat_statementspt-toolkitWAL

Sample challenges

What a Database Administrator (DBA) interview looks like.

Pick from our library or ask us to build a challenge for your stack. Each one is a real workspace, not a snippet.

Challenge 01

The replica that fell behind

Scenario

A streaming replica that lagged 90 seconds an hour ago. Logs, pg_stat_replication and disk metrics are open.

What you learn

Whether they suspect WAL volume before they touch the replica config.

In the workspace

$ ls challenges/

workspace, runbook.md, README.md

candidate has:

· a real Linux box in the browser
· kubectl, docker, terraform, jq, yq
· cluster, repo and cloud creds pre-wired
· auto-checks running in the background

interviewer sees:

· every keystroke + every command
· terminal + screen recording
· auto-graded pass/fail per check

AI in the loop

Score the engineer, and how they work with AI.

AI writes SQL fast and reasons about plans slowly. EasyEnv records prompts so you see whether the candidate read EXPLAIN against the LLM-suggested query before they decided to ship it.

Allow or block AI per question, not per interview

Full prompt and response history replayed in the review

Score "verifies AI output" as a separate signal

Ready to hire a Database Administrator (DBA) who ships?

Set up your first interview in under an hour. We will help you build a fit test for this role on your stack.

Request a Demo Create a Free Account

Role FAQ

Hiring a Database Administrator (DBA), answered.

Yes. MySQL, MariaDB, PostgreSQL and TimescaleDB are all available, with seeded data and a replica.

Yes. A WAL archive and base backup are pre-staged for PITR exercises.

No. The workspace runs in their browser. Terminal, editor, ports and dashboards are all served from the EasyEnv workspace, so candidate setup is zero.

Each challenge has automated checks (did the service come back, did the test pass, did the right log message appear) plus a recording your team can replay. Most reviews take under five minutes.

Yes. AI access is a per-interview setting. Block it for fundamentals, then allow it later in the loop to assess AI collaboration separately.

How to Hire a Database Administrator | EasyEnv | EasyEnv

Hire DBAswho actually keep the database honest

What you see when they work.

Three steps. Zero infra to maintain.

Pick the fit test

Send one link

Review at 2x

Why hiring a Database Administrator (DBA) is hard.

What we measure for a Database Administrator (DBA).

Slow query analysis

Index design

Replication health

Backup and restore

CLI fluency

AI collaboration

The stack we put in front of them.

What a Database Administrator (DBA) interview looks like.

The replica that fell behind

Score the engineer, and how they work with AI.

Ready to hire a Database Administrator (DBA) who ships?

Hiring a Database Administrator (DBA), answered.

Hire DBAswho actually keep the database honest

What you see when they work.

Three steps. Zero infra to maintain.

Pick the fit test

Send one link

Review at 2x

Why hiring a Database Administrator (DBA) is hard.

What we measure for a Database Administrator (DBA).

Slow query analysis

Index design

Replication health

Backup and restore

CLI fluency

AI collaboration

The stack we put in front of them.

What a Database Administrator (DBA) interview looks like.

The replica that fell behind

Score the engineer, and how they work with AI.

Ready to hire a Database Administrator (DBA) who ships?

Hiring a Database Administrator (DBA), answered.

Hire DBAs
who actually keep the database honest

Hire DBAs
who actually keep the database honest