Why I Joined Snowflake as a Solution Engineer

After several years of building data infrastructure at startups across Singapore, New York, and Seoul, I recently made a significant career move: joining Snowflake as a Solution Engineer.

Here is why.

The Decision

When I was considering my next move, I had several options:

• Continue on the IC (Individual Contributor) path as a senior/staff engineer
• Move into engineering management
• Transition to a customer-facing technical role

Each had its appeal, but the Solution Engineer role at Snowflake checked boxes I did not even know I had.

Why Solution Engineering?

1. Breadth of Problems

As a data engineer at a single company, you solve that company's problems. As a Solution Engineer, you see hundreds of different architectures, challenges, and use cases.

In my first few months, I have worked with:

• A major retailer optimizing their supply chain analytics
• A fintech building real-time fraud detection
• A healthcare company implementing data governance for compliance

Each engagement teaches me something new about how organizations use data.

2. Impact at Scale

At a startup, I might impact thousands of users. At Snowflake, the solutions I help design impact millions.

When you help an enterprise modernize their data platform, the ripple effects touch:

• Every analyst running queries
• Every dashboard refreshing
• Every ML model training
• Every business decision informed by data

3. The Perfect Middle Ground

Solution Engineering sits at the intersection of:

• Technical depth: You need to understand architecture, performance, security
• Business acumen: You need to understand what problems actually matter
• Communication: You need to explain complex concepts to diverse audiences

This matches how I like to work. Pure coding can feel disconnected from impact. Pure sales can feel disconnected from reality. SE work combines the best of both.

Why Snowflake?

The Product

I have been using and recommending Snowflake since 2022. The product genuinely solves real problems:

• Separation of storage and compute: Game-changer for cost optimization
• Zero-copy cloning: Makes development and testing so much easier
• Data sharing: The killer feature most people underutilize
• Snowpark: Python and other languages native in the warehouse

I am not just selling something I believe in - I am helping people use something that actually works.

The Market Position

Snowflake is at an interesting inflection point:

• Established enough to have enterprise credibility
• Growing fast enough that there is still room to make impact
• Investing heavily in AI/ML capabilities (Cortex, etc.)

The data platform market is consolidating, and Snowflake is well-positioned for the future.

The Team

Every person I met during the interview process was sharp, curious, and genuinely helpful. The culture feels collaborative rather than competitive.

What I Do Day-to-Day

A typical week might include:

Monday-Tuesday: Customer Engagements

• Technical deep-dives with engineering teams
• Architecture reviews and recommendations
• Proof-of-concept support

Wednesday: Internal Work

• Building demo environments
• Creating technical content
• Learning new features

Thursday-Friday: Mix

• Follow-ups with customers
• Team syncs and knowledge sharing
• Preparation for next week's engagements

No two weeks are the same, which keeps things interesting.

Lessons from the Transition

Technical Skills Transfer

Everything I learned as a data engineer is directly applicable:

• Understanding of data modeling
• Experience with ETL/ELT patterns
• Knowledge of performance optimization
• Familiarity with cloud platforms

The difference is now I apply these skills across many customers instead of one.

New Skills to Develop

Areas I am actively working on:

• Presentation skills: Explaining complex topics to executives
• Discovery skills: Understanding customer needs through questions
• Industry knowledge: Learning verticals I had not worked in before

The Mindset Shift

As an engineer, success is shipping features and maintaining systems. As an SE, success is helping customers succeed.

This sounds subtle but changes how you think:

• Less "here is how our product works"
• More "here is how our product solves your problem"

Advice for Engineers Considering SE Roles

If you are thinking about a similar transition:

Good signs it might be for you:

• You enjoy explaining technical concepts
• You are curious about different industries and use cases
• You want more variety in your work
• You are comfortable with ambiguity

Things to consider:

• You will write less code (but not zero code)
• Your schedule is less predictable
• Success metrics are different (customer outcomes vs. PRs merged)
• Travel may be required (varies by role/region)

How to prepare:

• Practice explaining technical concepts to non-technical people
• Learn about the business side of technology decisions
• Understand how companies evaluate and purchase software
• Build expertise in a domain (data platforms, in my case)

Looking Forward

I am excited about what is ahead:

• Helping enterprises modernize their data infrastructure
• Learning from hundreds of different architectures
• Contributing to Snowflake's product direction through customer feedback
• Building relationships across the Korean and APAC tech ecosystem

If you are working on data challenges and want to chat, feel free to reach out. Whether it is about Snowflake specifically or data architecture in general, I am always happy to connect.

Here is to the next chapter! ❄️