Principal Data Platform Architect
Data Engineer · Principal · Full Time
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Role
What you'll do.
Principal Data Platform Architect at Snowflake leading enterprise data architecture initiatives as an AI-native thinker. This role requires 10+ years of data engineering experience and 5+ years in pre-sales/solutions engineering, combining hands-on technical expertise with executive communication skills to drive Snowflake adoption across multi-cloud data platforms, lakehouse architectures, and real-time data integration at Fortune 500 enterprises.
Responsibilities
- Enterprise Data Architecture Leadership: Serve as a subject matter expert in cloud data platform design and architecture, presenting Snowflake technology and data engineering vision to C-suite executives, technical architects, and engineering teams at strategic enterprise prospects, customers, and key partners across multiple industries.
- Sales Cycle Technical Support and Pre-Sales Engineering: Work directly with the Sales organization and customer stakeholders to understand complex business requirements, strategize on navigating competitive sales cycles, develop value-based business cases, support enterprise proof-of-concepts (POCs), and provide technical guidance throughout the entire sales lifecycle from initial demonstrations to implementation planning.
- Solution Architecture and Design: Conduct deep-dive discovery sessions to analyze customer existing data infrastructure, identify architectural pain points, and design reference architectures showcasing Snowflake Data Platform capabilities across data ingestion, transformation, analytics, and lakehouse workloads aligned with customer business objectives.
- Technical Demonstrations and Proof-of-Concepts: Create compelling, hands-on technical demonstrations and execute complex proof-of-concept projects that validate Snowflake's multi-cloud data platform capabilities, clearly communicating value propositions and ROI to both technical and business audiences with impromptu whiteboarding expertise and polished presentations.
- Competitive Analysis and Market Positioning: Maintain deep understanding of the evolving data and analytics market landscape, competitive data warehousing solutions, complementary technologies, and emerging standards; develop positioning strategies that differentiate Snowflake's lakehouse, Data Mesh, and Data Fabric capabilities.
- Product and Marketing Collaboration: Partner cross-functionally with Product Management, Engineering, and Marketing teams to provide field insights, feedback on customer pain points, and recommendations for product enhancements, marketing messaging, and reference architecture improvements based on direct customer interactions.
- Best Practices Knowledge Transfer: Document and communicate industry best practices, reference architectures, and lessons learned from customer engagements to internal teams and customers, establishing Snowflake as a trusted advisor in data platform modernization and cloud data architecture.
Qualifications
What we look for.
Technical
SQL and Advanced Query Optimization
Expert-level SQL proficiency with deep understanding of query optimization, execution plans, window functions, and advanced analytics SQL patterns for complex data transformation and analysis at scale.
Python and Data Processing Libraries
Strong Python programming skills with expertise in pandas, NumPy, and data manipulation libraries; ability to write production-grade Python code for data processing and integration workflows.
Big Data Processing Frameworks
Hands-on expertise with distributed computing frameworks including Apache Spark, PySpark, Hadoop, Hive, and related big data technologies for large-scale data processing, transformation, and analytics.
Data Integration Tools and Platforms
Deep experience with enterprise data integration solutions including Apache NiFi, Matillion, Fivetran, Qlik, Informatica, and similar ETL/ELT platforms for building scalable, maintainable data pipelines.
Streaming Technologies
Proficiency with streaming data platforms including Apache Kafka, Apache Flink, Spark Streaming, AWS Kinesis, and related technologies for building real-time data pipelines and event-driven architectures.
Data Lakehouse Architecture
Expert understanding of modern data lakehouse design patterns, open table formats (Apache Iceberg, Delta Lake), Parquet columnar storage, and data mesh/fabric architectural paradigms for flexible, scalable data platforms.
Presentation and Communication Skills
Outstanding ability to communicate complex technical concepts to diverse audiences ranging from C-suite executives to senior engineers; expertise in whiteboarding architecture, creating compelling technical demonstrations, and presenting business value propositions.
Education
Bachelor's Degree Required
Bachelor's degree in Computer Science, Engineering, Mathematics, Computer Engineering, or related quantitative field required as foundation for technical depth.
Master's Degree Preferred
Master's degree in Computer Science, Engineering, Mathematics, or related technical discipline strongly preferred; equivalent advanced certifications or demonstrated expertise (such as cloud architecture certifications, data engineering specializations) acceptable.
Experience
10+ Years Enterprise Data Engineering
Extensive hands-on experience designing, building, and optimizing large-scale data warehouses, data lakes, and analytics platforms in production enterprise environments, demonstrating deep mastery of data architecture patterns, ETL/ELT methodologies, and data governance frameworks.
5+ Years Pre-Sales and Solutions Engineering
Proven track record as a Sales Engineer, Solutions Architect, or Solutions Engineer working directly with enterprise customers to understand requirements, design solutions, deliver POCs, and support deal closure within the data and analytics technology space.
Multi-Cloud Data Platform Experience
Hands-on experience architecting and implementing data solutions across multiple cloud providers (AWS, Azure, GCP), leveraging cloud-native services for data ingestion, storage, transformation, and analytics at enterprise scale.
Large-Scale Database and Data Warehouse Technology
Deep expertise with enterprise-grade database systems, cloud data warehousing platforms (Snowflake, Redshift, BigQuery, Synapse), and distributed data processing systems, including optimization, performance tuning, and scalability considerations.
ETL/ELT Pipeline Design and Implementation
Demonstrated experience designing and implementing complex data integration pipelines using modern ETL/ELT platforms and orchestration tools, ensuring data quality, reliability, and performance across enterprise data architectures.
Real-Time Data and Streaming Architecture
Practical experience designing and deploying real-time and near-real-time data pipelines, including change data capture (CDC) patterns, event-driven architectures, and streaming data integration use cases.
Skills
Required
Enterprise Data Architecture Design
Ability to design end-to-end data architectures that align with customer business strategy, technical constraints, and scalability requirements; expertise in creating reference architectures that become templates for implementations.
Technical Leadership and Influence
Demonstrated ability to lead technical discussions with senior stakeholders, influence architecture decisions, and establish credibility as a trusted technical authority among both customer and internal engineering teams.
Customer Requirements Gathering and Discovery
Advanced questioning and listening skills to uncover customer pain points, business drivers, and technical constraints; ability to translate business problems into data architecture solutions.
Solutions Selling and Business Acumen
Understanding of enterprise sales cycles and ability to articulate Snowflake's value proposition in business terms; skill in connecting product capabilities to customer ROI, cost savings, and competitive advantages.
Data Governance and Compliance
Understanding of enterprise data governance frameworks, data security, privacy regulations (GDPR, HIPAA, CCPA), and Snowflake's native governance capabilities for regulated industries.
Performance Optimization and Tuning
Expertise in database query optimization, workload management, resource allocation, and cost optimization strategies for cloud data platforms to maximize performance and efficiency.
Cross-Functional Collaboration
Strong ability to work effectively across Sales, Product, Marketing, and Engineering teams; translating customer feedback into product requirements and market positioning improvements.
Preferred
Snowflake Platform Expertise
Nice to haveDeep hands-on experience with Snowflake architecture, Snowpark, Streamlit, Iceberg integration, and advanced features; certifications such as Snowflake SnowPro Data Platform Architect strongly preferred.
Data Mesh and Fabric Architecture Patterns
Nice to haveExperience designing and implementing Data Mesh or Data Fabric architectures with federated governance models, domain-oriented data ownership, and self-service analytics platforms.
AI and Machine Learning Integration
Nice to haveExperience integrating AI/ML pipelines with data platforms, understanding of feature stores, model serving infrastructure, and agentic AI applications that leverage data warehousing capabilities.
Cloud Data Migration and Modernization
Nice to haveProven track record leading on-premises to cloud data platform migrations, data warehouse modernization initiatives, and technical debt reduction in legacy analytics infrastructure.
Industry-Specific Domain Expertise
Nice to haveDeep knowledge of data architecture patterns in specific industries such as Financial Services, Healthcare, Retail, or Manufacturing; understanding of industry-specific compliance and regulatory requirements.
Agile and Iterative Delivery
Nice to haveExperience working in agile environments with rapid iteration cycles, sprint-based development, and lean methodologies for delivering POCs and MVPs quickly.
AWS, Azure, or GCP Certifications
Nice to haveAdvanced certifications from major cloud providers (AWS Solutions Architect Professional, Azure Data Engineer Expert, GCP Professional Data Engineer) demonstrating deep cloud platform expertise.
Compensation
Pay and benefits.
Base·USD 189,000 – 248,062
Equity·Stock options
Benefits
Comprehensive Health Coverage
Medical, dental, and vision insurance with multiple plan options, Health Savings Account (HSA) with company contribution, and mental health support services through employee assistance programs.
Equity Compensation
Substantial stock options package providing ownership in Snowflake's growth; RSUs vested over 4-year schedule with annual refreshes aligned with career progression and performance.
Flexible Work Arrangements
Remote-first work culture with flexibility to work from home or utilize Snowflake offices in Menlo Park and other locations; flexible work schedule to support work-life integration.
Retirement Planning
401(k) plan with company matching contributions, financial planning resources, and retirement counseling to support long-term financial security.
Professional Development and Learning
Annual learning and development budget for conferences, certifications, and training; internal knowledge sharing programs, mentorship opportunities, and career development plans.
Paid Time Off
Generous paid time off policy including vacation days, sick days, and company holidays; parental leave, sabbatical options, and wellness time for work-life balance.
Wellness Programs
Fitness subsidies, wellness challenges, mental health resources, on-site/virtual wellness activities, and preventative health screenings to support employee wellbeing.
Commuter and Relocation Benefits
Commuter benefits for Bay Area employees, relocation assistance packages for candidates relocating to work at Menlo Park headquarters or other office locations.
Full posting
Original listing.
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.
Data Engineering - Applied Field Engineer- CA- Menlo Park- Remote
Snowflake is about empowering enterprises to achieve their full potential — and people too. With a culture that’s all in on impact, innovation, and collaboration, Snowflake is the sweet spot for building big, moving fast, and taking technology — and careers — to the next level.
Our Solution Engineering organization is seeking a Data Engineering Specialist to join our Applied Field Engineering team who can provide technical leadership in working with both technical and business executives in the design and architecture of the Snowflake Cloud Data Platform as a critical component of their enterprise data architecture and overall ecosystem. In this role you will work directly with the sales team to understand the needs of our customers, strategize on how to navigate winning sales cycles, provide compelling value-based demonstrations, support enterprise Proof of Concepts, and ultimately close business. You will leverage your expertise, best practices and reference architectures highlighting Snowflake’s Data Platform capabilities across data ingestion, transformation, and lakehouse workloads. You are equally comfortable in both a business and technical context, interacting with executives and talking shop with technical audiences.
IN THIS ROLE YOU WILL GET TO:
Apply your multi-cloud data architecture expertise while presenting Snowflake technology and vision to executives and technical contributors at strategic prospects, customers, and partners
Work hands-on with prospects and customers to demonstrate and communicate the value of Snowflake technology throughout the sales cycle, from demo to proof of concept to design and implementation
Immerse yourself in the ever-evolving industry, maintaining a deep understanding of competitive and complementary technologies and vendors and how to position Snowflake in relation to them
Collaborate with Product Management, Engineering, and Marketing to continuously improve Snowflake’s products and marketing
ON DAY ONE, WE WILL EXPECT YOU TO HAVE:
10+ years of architecture and data engineering experience within the Enterprise Data space
5+ years experience within a pre-sales environment (Sales Engineer, Solutions Engineer, Solutions Architect, etc…)
Outstanding presentation skills to both technical and executive audiences, whether impromptu on a whiteboard or using presentations and demos.
Ability to connect a customer’s specific business problems and Snowflake’s solutions
Ability to do deep discovery of customer’s architecture framework and connect those with Snowflake Data Architecture.
Broad range of experience within large-scale Database and/or Data Warehouse technology, ETL, analytics and cloud technologies. For example, Data Lake, Data Mesh, Data Fabric
Hands on Development experience with technologies such as SQL, Python, Pandas, Spark, PySpark, Hadoop, Hive and any other Big data technologies
Deep understanding of data integration services and tools for building ETL and ELT data pipelines such as Apache NiFi, Matillion, Fivetran, Qlik, or Informatica.
Familiarity with streaming technologies (ex. Kafka, Flink, Spark Streaming, Kinesis) and real-time or near real time use cases (ex. CDC)
Experience designing interoperable data lakehouse architectures and experience working with Iceberg, Delta, and Parquet
Strong architectural expertise in data engineering to confidently present and demo to business executives and technical audiences, and effectively handle any impromptu questions
Bachelor’s Degree required, Masters Degree in computer science, engineering, mathematics or related fields, or equivalent experience preferred
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
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