Senior Solution Engineer
Snowflake is hiring a Senior Solution Engineer for a remote role open to applicants in United States. It pays $165k-$217k a year and Level rates it ; you can apply on Snowflake.
Level's read on this job
- Level rates this role Works on AI ●●●○: the daily work is on AI products, without building the model.
- This is listed as a remote role.
- The posting mentions Snowpark, Cortex AI and SQL among its tools and skills.
- Level classes it as a senior role.
- Snowflake has 354 other open roles on Level.
AI in this role
Drive enterprise data architecture and AI-powered solutions as a Senior Solution Engineer at Snowflake.
At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done.
We are looking for a Senior Solution Engineer who thrives at the intersection of data, AI, and complex enterprise architecture. In this role you will work directly with the sales team and channel partners to understand the data challenges of our customers, strategize on how to navigate winning sales cycles, deliver compelling data-driven demonstrations, and support enterprise Proof of Concepts that showcase measurable business outcomes.
As a Snowflake Solution Engineer you must share our passion for transforming how organizations use data — from raw ingestion to real-time analytics to AI-powered applications. You thrive in a dynamic environment, are equally comfortable whiteboarding a medallion architecture with a data engineering team and presenting data ROI to a C-suite, and you bring deep opinions about what good data platform design looks like.
IN THIS ROLE YOU WILL GET TO:
Present Snowflake's Data Cloud vision to data engineering leaders, analytics teams, data scientists, and executive stakeholders at prospects and customers
Lead hands-on technical discovery to map a customer's existing data architecture — pipelines, warehouses, lakehouses, governance gaps — and design a Snowflake-native path forward
Build and deliver tailored demos and proof of concepts across Snowflake's full data platform: data engineering (Snowpark, Dynamic Tables, Snowpipe), AI/ML (Cortex AI, ML model registry), and data sharing (Data Clean Rooms, Marketplace listings)
Guide customers through modern data architecture patterns including Data Mesh, Data Lakehouse, real-time streaming pipelines, and unified governance frameworks
Translate ambiguous business problems — churn prediction, supply chain visibility, financial consolidation, operational analytics — into concrete Snowflake data solutions
Partner with Product Management, Engineering, and Field teams to feed customer data architecture patterns back into the product roadmap
ON DAY ONE WE WILL EXPECT YOU TO HAVE:
7–8 years of industry experience, with a minimum of 5 years in a pre-sales or solutions architecture role focused on data platforms
Deep hands-on expertise with SQL, Python, and cloud data warehouse / data lakehouse architectures; able to write working code in a customer session without hesitation
Broad experience across the modern data stack: ETL/ELT tools (dbt, Fivetran, Informatica, Spark), streaming platforms (Kafka, Kinesis), orchestration (Airflow, dbt Cloud), BI tools (Tableau, Looker, Power BI), and cloud infrastructure (AWS, Azure, GCP)
Proven ability to conduct deep data architecture discovery — understanding a customer's source systems, transformation layers, consumption patterns, and governance requirements — and connect those findings to a Snowflake reference architecture
Experience positioning AI and ML capabilities within a data platform context: feature stores, model training pipelines, LLM-powered applications, and AI governance
Strong intuition for data governance, quality, and compliance challenges (GDPR, CCPA, PCI) and how platform design decisions affect them
Ability to quantify the business value of a modern data architecture — cost reduction, time-to-insight, pipeline reliability, data product monetization
A demonstrated track record using AI code generation tools to accelerate prototyping and proof-of-concept delivery
University degree in computer science, data science, engineering, mathematics or a related field, or equivalent practical experience. A Master's in Data Science or Business Analytics is a plus
Experience working with GSIs (EY, Deloitte, Accenture, Slalom, etc.) on large data platform programs is beneficial but not required
COMPENSATION & BENEFITS:
$220,000 - $288,000 OTE (On Target Earnings = Base Salary + Commission/Quota)
Snowflake offers competitive base salary, variable compensation, equity, and comprehensive benefits including 401(k), health/dental/vision, flexible PTO, and professional development budget.
ABOUT OUR TEAM:
Our Solution Engineers are customer-obsessed data practitioners. We believe in rigorous discovery before prescribing solutions, we stay honest about what Snowflake can and can't do, and we hold ourselves accountable to outcomes — not just demos. We love to learn, give and receive direct feedback, and are relentless about making our customers' data more accessible, reliable, and valuable. If you have strong opinions about data architecture and enjoy proving them with working code, you'll fit right in.
ABOUT SNOWFLAKE:
Snowflake started with a clear vision: make modern data warehousing effective, affordable, and accessible to all data users. Today the Snowflake Data Cloud goes far beyond warehousing — it's where organizations build data pipelines, run ML workloads, share live data across the ecosystem, and power AI applications, all on a single governed platform. Our built-for-the-cloud architecture delivers the performance of a data warehouse, the flexibility of a data lake, and the elasticity of the cloud at a fraction of traditional costs.
Snowflake is growing fast, and we’re scaling our team to help enable and accelerate our growth. We are looking for people who share our values, challenge ordinary thinking, and push the pace of innovation while building a future for themselves and Snowflake.
How do you want to make your impact?
For jobs located in the United States, please visit the job posting on the Snowflake Careers Site for salary and benefits information: careers.snowflake.com
How we rate this
Senior Solution Engineer at Snowflake rates 65 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Questions you could be asked
- Tell me about a project where data architecture was part of your work. What did you do?
- Tell me about a project where presales was part of your work. What did you do?
- Tell me about a project where proof of concept was part of your work. What did you do?
- Tell me about a project where data engineering was part of your work. What did you do?
- Tell me about a project where machine learning was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: Data Architecture, Presales, Proof Of Concept, Data Engineering, and Machine learning. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.
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