Data Engineering Solutions Specialist
Snowflake is hiring a Data Engineering Solutions Specialist for a remote role open to applicants in United States. It pays $154k-$202k a year and Level rates it ; you can apply on Snowflake.
Level's read on this job
- Level rates this data engineer role Little AI ●○○○: aI is not part of the work.
- Pay on this posting starts 5% higher than the typical data engineer posting on Level.
- This is listed as a remote role.
- The posting mentions Openflow, Apache Iceberg and Polaris among its tools and skills.
- Snowflake has 367 other open roles on Level.
AI in this role
Drive sales execution and customer adoption for Snowflake's data engineering and data lakehouse workloads.
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.
Snowflake is seeking an accomplished Principal level Data Engineering Solutions Specialist (Openflow and Iceberg/Polaris) to drive sales execution for our ingestion workloads. This is a strategic role that works closely with the broader field organization to ensure the successful customer adoption of Snowflake’s Data Engineering and Data Lake capabilities.
Responsibilities:
Achieve pipeline generation and revenue targets for allocated accounts and/or territory on a quarterly and annual basis by developing a sales strategy in the allocated territory with a target account list
Execute tailored sales plays to capture market opportunities in Data Engineering, helping customers optimize their use of Snowflake's platform.
Work directly with customers to understand their Data Engineering needs, communicating insights to inform Snowflake’s product roadmap and ensuring alignment with customer requirements.
Become an expert in Snowflake’s Data Engineering and Data Lakehouse capabilities and provide executive-level insights to customers and partners, guiding strategic discussions that emphasize the value of Snowflake’s Data Engineering capabilities.
Work with our Account Executives, Sales Engineers, Leadership and Field CTOs to drive customer engagements from discovery and qualification through solution implementation and deployment
Track, analyze, and report on Data Engineering sales performance metrics, using data-driven insights to optimize strategies and drive continuous improvement
Partner with the broader cross-functional organization to integrate Data Engineering sales efforts with Snowflake’s overall go-to-market plans.
Driving the forecast of the region and exceeding revenue targets on consumption
Minimum Qualifications:
10+ years of professional experience and at least 6 of years sales experience with consistently exceeding sales objectives selling technical solutions and software products into the enterprise market
A strong track record of meeting or exceeding revenue targets in highly competitive markets
A familiarity with solution-based approach to selling, have experience managing a complex sales process and possess excellent presentation and listening skills, organization and contact management capabilities
Proven ability to independently manage, develop, and close new client relationships
Strong presentation and communication skills, capable of engaging with senior executives and key decision-makers at both technical and business levels.
In-depth knowledge of Data Engineering, Data Lakehouse, Ingestion and Transformation technologies, with proven expertise in driving successful sales initiatives within these domains
Strong ability to work across cross-functional teams including Sales Engineering, Professional Services, Marketing, and Product
Preferred Qualifications:
Experience operating in overlay sales role and/or driving product consumption through workloads and use cases
Technical background with an understanding of the data space and market
Bachelor’s Degree
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
Data Engineering Solutions Specialist at Snowflake rates 25 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.
Little AI. AI is not part of the work.
- ●●●● 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
Pay
- This job starts at
- $154k
- Typical data engineer job
- $146k
This posting starts 5% above the typical data engineer job. See data engineer jobs
Questions you could be asked
- Tell me about a project where data engineering was part of your work. What did you do?
- Tell me about a project where sales strategy was part of your work. What did you do?
- Tell me about a project where pipeline generation was part of your work. What did you do?
- Tell me about a project where data lakehouse was part of your work. What did you do?
- Tell me about a project where client engagement was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: Data Engineering, Sales Strategy, Pipeline Generation, Data Lakehouse, and Client Engagement. 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.
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