Interviews/Data & Analytics/Snowflake Developer

Hire Snowflake Developers
who actually ship Snowflake that costs less than it earns

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.

SnowflakeSQLWarehouse sizingClustering · searchLive 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 Snowflake developer reads query plans before they resize warehouses. The good ones cluster with intent, watch the credit meter, and never trust auto-suspend to fix a hot pipeline. EasyEnv hands the candidate a real Snowflake account with a runaway query and a finance ticket.

Inside a live interview

What you see when they work.

Real Snowflake account, real query plan, every command 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@snowflake-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 Snowflake Developer is hard.

Snowflake depth hides under "I write SQL". Plans show the difference.

Warehouse sizing is folklore for most.

Clustering, search optimization and result cache each have their place.

Cost-aware design is a real signal.

The fit test

What we measure for a Snowflake Developer.

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

Query plan reading

A query at 4 minutes that should be 4 seconds. They read the plan.

Warehouse sizing

A pipeline that bursts a small. They size up and down on purpose.

Clustering

A multi-TB table with bad pruning. They cluster on the right column.

Security and masking

A column-level masking policy that leaks. They tighten.

Streams and tasks

A CDC stream consumed twice. They explain offsets.

AI collaboration

Allow AI for SQL refactors and grade whether they ran EXPLAIN after.

The stack we put in front of them.

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

SnowflakeSnowSQLSnowparkStreams · TasksTime TravelDynamic TablesExternal TablesSearch OptimizationClusteringResource MonitorsMasking PoliciesRow Access PoliciesCDC

Sample challenges

What a Snowflake Developer 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 4TB scan

Scenario

A query that scans 4TB when it should scan 40GB. The plan is open.

What you learn

Whether they cluster with reason and prove the prune.

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 Snowflake SQL that compiles and scans everything. EasyEnv records prompts so you see whether the candidate ran EXPLAIN after the LLM-suggested change.

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 Snowflake Developer 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 Snowflake Developer, answered.

Yes. On enterprise plans we can federate to your account with a scoped role.

Yes. Snowpark for Python and Cortex ML can be pre-wired.

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/Data & Analytics/Snowflake Developer

Hire Snowflake Developers
who actually ship Snowflake that costs less than it earns

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.

SnowflakeSQLWarehouse sizingClustering · searchLive 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 Snowflake account, real query plan, every command 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@snowflake-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 Snowflake Developer is hard.

Snowflake depth hides under "I write SQL". Plans show the difference.

Warehouse sizing is folklore for most.

Clustering, search optimization and result cache each have their place.

Cost-aware design is a real signal.

The fit test

What we measure for a Snowflake Developer.

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

Query plan reading

A query at 4 minutes that should be 4 seconds. They read the plan.

Warehouse sizing

A pipeline that bursts a small. They size up and down on purpose.

Clustering

A multi-TB table with bad pruning. They cluster on the right column.

Security and masking

A column-level masking policy that leaks. They tighten.

Streams and tasks

A CDC stream consumed twice. They explain offsets.

AI collaboration

Allow AI for SQL refactors and grade whether they ran EXPLAIN after.

The stack we put in front of them.

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

SnowflakeSnowSQLSnowparkStreams · TasksTime TravelDynamic TablesExternal TablesSearch OptimizationClusteringResource MonitorsMasking PoliciesRow Access PoliciesCDC

Sample challenges

What a Snowflake Developer 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 4TB scan

Scenario

A query that scans 4TB when it should scan 40GB. The plan is open.

What you learn

Whether they cluster with reason and prove the prune.

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 Snowflake SQL that compiles and scans everything. EasyEnv records prompts so you see whether the candidate ran EXPLAIN after the LLM-suggested change.

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 Snowflake Developer 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 Snowflake Developer, answered.

Yes. On enterprise plans we can federate to your account with a scoped role.

Yes. Snowpark for Python and Cortex ML can be pre-wired.

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 Snowflake Developer | Warehouse · Cost Interviews | EasyEnv | EasyEnv

Hire Snowflake Developerswho actually ship Snowflake that costs less than it earns

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 Snowflake Developer is hard.

What we measure for a Snowflake Developer.

Query plan reading

Warehouse sizing

Clustering

Security and masking

Streams and tasks

AI collaboration

The stack we put in front of them.

What a Snowflake Developer interview looks like.

The 4TB scan

Score the engineer, and how they work with AI.

Ready to hire a Snowflake Developer who ships?

Hiring a Snowflake Developer, answered.

Hire Snowflake Developerswho actually ship Snowflake that costs less than it earns

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 Snowflake Developer is hard.

What we measure for a Snowflake Developer.

Query plan reading

Warehouse sizing

Clustering

Security and masking

Streams and tasks

AI collaboration

The stack we put in front of them.

What a Snowflake Developer interview looks like.

The 4TB scan

Score the engineer, and how they work with AI.

Ready to hire a Snowflake Developer who ships?

Hiring a Snowflake Developer, answered.

Hire Snowflake Developers
who actually ship Snowflake that costs less than it earns

Hire Snowflake Developers
who actually ship Snowflake that costs less than it earns