Account Engineer

Snowflake2 days ago

Location

US-CO-Denver

Workplace

Remote

Type

Full Time

Salary

USD 105,000 – 137,812

Level

Junior

Role

Sales Engineer

Posted

Jul 10, 2026

Full TimeRemoteJunior

The role

Summary

Account Engineer at Snowflake is a customer-facing technical role focused on delivering expertise and building relationships with prospects and customers exploring the Snowflake AI Data Cloud. You'll blend technical problem-solving with collaboration, supporting technical evaluations, proof-of-concept demonstrations, and helping customers align Snowflake solutions with their business outcomes. The role requires foundational experience in technical fields like solution engineering or software development, with basic SQL/Python knowledge, and offers significant mentorship and career development opportunities in a fast-growing data platform company.

What you'll do

Technical Customer Presentations: Present and communicate Snowflake's AI Data Cloud technology, vision, and capabilities to diverse stakeholder audiences ranging from technical individual contributors to C-level business leaders. Translate complex technical concepts into business value propositions that resonate with different buyer personas while developing your skills in audience-specific communication strategies.

Technical Evaluation Support: Collaborate with customers to plan, design, and execute technical evaluations, proof-of-concept demonstrations, and hands-on labs. Work alongside senior team members to architect solutions, configure Snowflake environments, and showcase practical capabilities that address customer-specific requirements and use cases.

Customer Relationship Building: Foster trust and long-term relationships with prospects, customers, and technical champions. Serve as a technical liaison between customer teams and Snowflake's sales and success organizations. Champion Snowflake's platform capabilities while actively understanding and addressing customer challenges and business objectives.

Technical Expertise Development: Continuously expand technical proficiency in Snowflake's platform, modern data technologies, cloud infrastructure, and AI/ML workflows. Stay current on industry trends, competitive data platforms, emerging technologies, and best practices within the data engineering and analytics landscape.

Cross-Functional Collaboration: Work closely with Account Executives, Marketing teams, and Snowflake's partner ecosystem to ensure customers successfully realize and maximize the value of Snowflake. Coordinate between customer technical teams and internal resources to remove blockers and drive successful implementations.

Solution Design Contributions: Contribute to developing and refining technical solutions that align with customer requirements. Help design future-state architectures and implementation roadmaps, learning to balance technical elegance with business pragmatism and customer constraints.

What we look for

Technical

SQL FundamentalsSolid understanding of SQL query writing, database concepts, and data manipulation. Ability to write and optimize basic to intermediate SQL queries for data analysis and demonstration purposes.

Python Programming BasicsWorking knowledge of Python for data manipulation, scripting, and automation. Familiarity with data science libraries and ability to read and understand Python code used in data workflows.

Cloud Platform ArchitectureUnderstanding of public cloud platforms (AWS, Azure, GCP) including core services, infrastructure concepts, networking, and how data platforms integrate within cloud ecosystems.

Data Technologies EcosystemFamiliarity with modern data stack tools including data warehouses (Snowflake, BigQuery, Redshift), data integration platforms (Databricks, Apache Spark), CI/CD tooling, containerization (Docker), and orchestration tools.

Data Engineering ConceptsBasic understanding of data engineering principles, ETL/ELT workflows, data pipeline design, and data quality frameworks. Knowledge of how data flows through modern architectures.

Education

Bachelor's Degree in Computer Science, Engineering, or Related FieldPreferred foundational education in computer science, software engineering, data science, mathematics, or similar technical discipline that demonstrates analytical and problem-solving capabilities.

Technical Certification or TrainingRelevant certifications such as cloud platform certifications (AWS Solutions Architect Associate, Azure Fundamentals), data engineering certifications, or Snowflake University certifications are valuable but not required.

Experience

Solution Engineering or Technical Sales BackgroundPrior experience in solution engineering, pre-sales engineering, or similar customer-facing technical roles where you've presented technical solutions and supported customer evaluations.

SaaS or Data Technology Experience1-3 years of experience working with SaaS platforms, data analytics solutions, cloud technologies, or data warehousing platforms. This could include roles in software development, solutions architecture, or data engineering.

Customer-Facing Technical RoleBackground in technical roles requiring direct customer interaction, relationship building, and the ability to communicate complex technical concepts to non-technical stakeholders. Examples include technical support, solutions architecture, or technical account management.

Skills

Required skills

SQLFoundational SQL query writing and database fundamentals required for technical demonstrations and customer evaluations.

Technical CommunicationAbility to clearly articulate complex technical concepts to diverse audiences including technical and non-technical stakeholders, both verbally and in writing.

Problem-SolvingStrong analytical and critical thinking skills to understand customer challenges, design appropriate technical solutions, and troubleshoot issues that arise during evaluations.

Customer FocusGenuine interest in understanding customer business objectives, pain points, and success metrics. Ability to align technical capabilities with measurable business outcomes.

CollaborationStrong teamwork and interpersonal skills with ability to work effectively across diverse teams including sales, marketing, product, and customer organizations.

Nice to have

PythonWorking knowledge of Python for data manipulation, automation, and integration with data platforms. Experience with data science libraries and notebook environments like Jupyter.

Snowflake Platform KnowledgeHands-on experience with Snowflake, including warehouse configuration, query optimization, and feature functionality. Familiarity with Snowflake's AI Data Cloud capabilities and recent product innovations.

Apache SparkUnderstanding of Apache Spark for distributed data processing, performance tuning, and integration with modern data platforms and cloud infrastructure.

DevOps and CI/CD ToolsFamiliarity with version control systems (Git), continuous integration/continuous deployment practices, containerization (Docker, Kubernetes), and infrastructure-as-code concepts.

Data Science and Machine LearningUnderstanding of ML workflows, model development, feature engineering, and governance frameworks. Knowledge of how data platforms support AI/ML initiatives and retrieval augmented generation (RAG).

Data Governance and SecurityFamiliarity with data governance frameworks, data lineage, access control, compliance requirements, and security best practices in cloud data platforms.

Databricks and Alternative PlatformsExperience with competing or complementary data platforms like Databricks, Azure Fabric, Google BigQuery, or Amazon Redshift to provide competitive context during customer discussions.

Compensation & benefits

Salary

USD 105,000 – 137,812 (annual)

Stock options

Available

Benefits

Equity Compensation

Significant equity stake in Snowflake as part of your total compensation package, allowing you to share in the company's growth and success as a public company in the high-growth data analytics space.

Comprehensive Health Benefits

Medical, dental, and vision insurance coverage with competitive plans to support your overall wellness and healthcare needs.

401(k) Retirement Plan

Tax-advantaged retirement savings plan with potential company matching contributions to help you build long-term financial security.

Flexible Time Off

Flexible PTO policy allowing you to balance work and personal life, with the understanding that you manage your time responsibly in this customer-facing role.

Professional Development Budget

Dedicated annual budget for training, certifications, conference attendance, and skill development to support your career growth in the data technology space.

Mentorship and Learning Programs

Structured mentorship from experienced team members, access to Snowflake University learning resources, hands-on labs, and internal training programs designed to accelerate your technical and professional development.

Collaborative Work Environment

Supportive team culture prioritizing learning, curiosity, and growth mindset with emphasis on inclusion, empathy, and mutual respect across the organization.

Career Development Opportunities

Clear pathways to advance from Account Engineer into Senior Account Engineer, Solutions Architect, or Sales Engineering leadership positions as you develop expertise and experience.

Interview process

1
Initial Phone Screening — Conversation with a recruiter to discuss your background in technical roles, interest in customer-facing positions, and alignment with Snowflake's AI-native culture. Expect questions about your experience with data technologies, cloud platforms, and customer interactions.
2
Technical Aptitude Assessment — Screening to evaluate your technical foundation including SQL queries, Python fundamentals, and understanding of cloud data platforms. May include practical coding exercises or technical problem-solving scenarios related to data engineering concepts.
3
Sales Engineering Manager Interview — In-depth conversation with the hiring manager covering your problem-solving approach, communication skills for diverse audiences, and ability to balance technical depth with business acumen. Expect real-world scenarios involving customer challenges and solution design.
4
Peer Team Interview — Interview with current Account Engineers or Solutions Architects to assess team fit, collaboration style, and cultural alignment. Discussion of how you'd handle customer interactions, support from peers, and your approach to learning new technologies.
5
Customer Scenario Presentation — Presentation or discussion where you address a realistic customer scenario involving technical evaluation, proof-of-concept planning, or solution architecture. This assesses your ability to think through customer problems and communicate technical solutions effectively.
6
Final Leadership Round — Conversation with senior leadership in Sales Engineering or Customer Success to discuss your career aspirations, growth mindset, and long-term fit within Snowflake's organization and vision for the data platform industry.