Principal Software Engineer II, Data Platform (Streaming, Dynamic Tables and more)

SnowflakeYesterday

Location

DE-Berlin-Trion Building

Type

Full Time

Salary

USD 250,000 – 350,000

Level

Principal

Role

Principal Engineer

Posted

Jun 29, 2026

Full TimePrincipal

The role

Summary

Principal Software Engineer II leading the evolution of Snowflake's Data Platform with focus on streaming ingestion, dynamic tables, and real-time data movement at cloud scale. This role combines technical architecture leadership, distributed systems expertise, and hands-on engineering to define platform strategy and mentor senior engineers across critical data processing initiatives.

What you'll do

Technical Strategy & Architecture Leadership: Drive the technical strategy and architecture for key Data Platform initiatives, focusing on real-time data movement and incremental processing at cloud scale. Set the direction for streaming ingestion and transformation capabilities that serve thousands of customers globally.

Design & Engineering Standards: Lead comprehensive design reviews and establish engineering standards across distributed teams. Create architectural guidelines and best practices for building scalable, resilient data systems that handle petabyte-scale workloads.

Technical Problem Solving: Identify and resolve high-impact technical challenges and systemic bottlenecks in dynamic tables infrastructure. Focus on reducing latency, improving efficiency, and optimizing performance across Snowflake's multi-tenant cloud platform.

Mentorship & Team Development: Mentor and grow senior engineers within the Data Platform organization. Raise the engineering bar through code reviews, technical guidance, and creating learning opportunities that develop future technical leaders.

Cross-Functional Collaboration: Partner closely with product, infrastructure, and customer-facing leadership on roadmap planning and technical direction. Influence organizational strategy based on platform capabilities and customer requirements.

Hands-On Engineering Delivery: Maintain continuous hands-on technical contributions in the most critical areas of the platform. Build and implement solutions for streaming infrastructure, incremental materialization algorithms, and real-time data processing systems.

What we look for

Technical

Distributed Systems ArchitectureDeep expertise in designing distributed systems including consistency models, fault tolerance, replication strategies, and consensus algorithms. Experience with tradeoffs between strong consistency, eventual consistency, and causal consistency.

Real-Time Data ProcessingAdvanced knowledge of streaming architectures, event processing systems, windowing semantics, state management, and exactly-once/at-least-once delivery guarantees. Experience with micro-batching and continuous operator models.

Data Platform InfrastructureHands-on experience building or operating large-scale data platform infrastructure. Knowledge of table formats, query engines, metadata systems, and data catalog infrastructure for analytics workloads.

Performance OptimizationExpertise in identifying and resolving latency bottlenecks in complex systems. Experience profiling, benchmarking, and optimizing query execution, data movement, and resource utilization across cloud infrastructure.

Education

Computer Science or Related Field (Preferred)Bachelor's degree in Computer Science, Computer Engineering, Mathematics, or equivalent field preferred. Advanced degree or extensive self-directed study in distributed systems, databases, or systems architecture is valued.

Experience

14+ Years Software EngineeringFourteen or more years of progressive software engineering experience with proven expertise in designing, building, and operating distributed systems at scale. Track record of growing from senior engineer to principal-level engineer with increasing architectural responsibility.

Platform-Scale Initiative DeliveryDemonstrated track record of defining, architecting, and delivering platform-scale technical initiatives that impact millions of users or customers. Experience shipping major versions of platform features or infrastructure components.

Streaming & Batch Data SystemsExpert-level knowledge of streaming and/or batch data systems such as Apache Flink, Apache Spark, or equivalent frameworks. Specialized knowledge in incremental materialization algorithms, changedata capture, and real-time transformation patterns.

Cross-Layer Systems ThinkingStrong systems thinking with ability to reason across multiple layers of complexity including infrastructure, storage engines, compute optimization, and API design. Experience optimizing end-to-end data pipelines across heterogeneous cloud environments.

Organizational InfluenceProven experience influencing technical direction across large organizations and multiple teams. Track record of building consensus around complex architectural decisions and driving adoption of new technical approaches.

Customer EngagementPassion for directly engaging with customers to understand use cases, gather requirements, and extract insights that inform product direction. Experience translating customer feedback into technical requirements.

Skills

Required skills

Apache Flink or SparkExpert-level proficiency with Apache Flink, Apache Spark, or functionally equivalent stream processing frameworks. Deep understanding of framework internals, operator graphs, and optimization opportunities.

Distributed Systems DesignMastery of distributed systems principles including CAP theorem, consensus algorithms, replication, and failure handling. Ability to evaluate architectural tradeoffs for resilience and scalability.

Incremental Processing & MaterializationAdvanced knowledge of incremental computation, change propagation, and materialized view maintenance. Understanding of differential dataflow, trickle semantics, and watermark handling.

Scala or Java Backend DevelopmentExpert-level proficiency in Scala and/or Java for building high-performance backend systems. Deep understanding of concurrency models, memory management, and performance tuning in the JVM ecosystem.

Technical Architecture & DesignStrong capability in designing system architectures, conducting design reviews, and communicating complex technical concepts. Experience creating architectural decision records and technical specifications.

Cloud Infrastructure & DevOpsStrong hands-on experience with cloud platforms including AWS, GCP, or Azure. Understanding of containerization, Kubernetes orchestration, and cloud-native deployment patterns.

Nice to have

AI-Augmented Development & LLM IntegrationExperience incorporating artificial intelligence and large language models into engineering workflows. Familiarity with AI-assisted coding tools, prompt engineering, and AI-native development practices.

Snowflake Platform InternalsFamiliarity with Snowflake platform architecture, including query optimization, metadata systems, and cloud-native data warehouse design patterns. Previous experience working with or contributing to Snowflake systems is valuable.

Metadata Systems & Query OptimizationExperience designing or operating metadata systems, data catalogs, or query optimization infrastructure. Knowledge of cost-based query optimization, plan generation, and statistics management.

Apache Open Source ContributionsContributions to top-level Apache projects or other open-source systems projects. Track record of shipping production-grade code and engaging in technical community leadership.

Data Catalog & Lineage SystemsExperience building or working with data catalog infrastructure, data lineage systems, and metadata management for analytics platforms. Understanding of data governance and discoverability challenges.

Compensation & benefits

Salary

USD 250,000 – 350,000 (annual)

Stock options

Available

Benefits

Comprehensive Health Benefits

Medical, dental, and vision coverage with competitive premiums and low deductibles. Includes preventive care, wellness programs, and mental health services.

Retirement Planning

401(k) plan with generous company matching contributions. Early access to retirement planning resources and financial advisory services.

Flexible Time Off

Unlimited paid time off policy plus paid holidays. Work-life balance support and flexible scheduling to accommodate personal needs.

Equity & Stock Options

Competitive equity package as a publicly-traded company. Stock purchase plans and performance-based equity grants to align incentives with long-term growth.

Professional Development

Learning and development budget for conferences, courses, and certifications. Tuition reimbursement and internal technical training programs.

Remote Work Flexibility

Hybrid and remote work options providing flexibility in work location and schedule. Collaboration tools and home office stipends for remote workers.

Parental Leave

Paid parental leave for birth and adoption. Support programs for working parents including backup childcare assistance.

Commuter & Wellness Benefits

Pre-tax commuter benefits, on-site wellness facilities or subsidies, and fitness center memberships to support employee health and wellbeing.

Interview process

1
Initial Recruiter Screening — Preliminary conversation with Snowflake recruiter to discuss background, career trajectory, and alignment with the Principal Engineer role. Focus on understanding your experience with distributed systems and data platforms.
2
Technical Screening Call — Technical conversation with a senior engineer from the Data Platform team. Discussion of past projects, architectural decisions, and technical depth in streaming systems, real-time processing, or data platform infrastructure.
3
System Design Interview — In-depth technical interview focused on distributed systems design. Design a large-scale data streaming system, discuss tradeoffs between consistency and performance, and explain your architectural reasoning.
4
Deep Dive Technical Discussion — Conversation with multiple engineers from the Data Platform and infrastructure teams. Discuss specific technical challenges, review code samples or past projects, and explore problem-solving approaches for real platform challenges.
5
Architecture & Strategy Discussion — Senior leadership interview with principal or staff engineers and engineering managers. Discussion of long-term platform vision, technical strategy formulation, and your experience influencing technical direction across organizations.
6
Customer & Product Collaboration Round — Conversation with product management and customer engineering stakeholders. Understand how you gather customer insights, translate requirements into technical initiatives, and balance customer needs with platform constraints.
7
Leadership & Values Assessment — Final round with hiring manager and senior leadership. Discussion of team leadership, mentoring philosophy, communication style, and alignment with Snowflake's culture of innovation and AI-native thinking.
8
Offer & Negotiation — Compensation discussion including base salary, equity package, and benefits. Opportunity to negotiate role scope, team structure, or strategic focus areas.