Scale Engineer

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

Principal Engineer · Principal · Full Time

DE-Berlin-Trion BuildingUSD 250k – 350k1mo ago
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Role

What you'll do.

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.

Responsibilities

  • 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.

Qualifications

What we look for.

Technical

  • Distributed Systems Architecture

    Deep 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 Processing

    Advanced 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 Infrastructure

    Hands-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 Optimization

    Expertise 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 Engineering

    Fourteen 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 Delivery

    Demonstrated 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 Systems

    Expert-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 Thinking

    Strong 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 Influence

    Proven 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 Engagement

    Passion 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

  • Apache Flink or Spark

    Expert-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 Design

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

  • Incremental Processing & Materialization

    Advanced knowledge of incremental computation, change propagation, and materialized view maintenance. Understanding of differential dataflow, trickle semantics, and watermark handling.

  • Scala or Java Backend Development

    Expert-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 & Design

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

  • Cloud Infrastructure & DevOps

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

Preferred

  • AI-Augmented Development & LLM Integration

    Nice to have

    Experience 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 Internals

    Nice to have

    Familiarity 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 Optimization

    Nice to have

    Experience 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 Contributions

    Nice to have

    Contributions 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 Systems

    Nice to have

    Experience building or working with data catalog infrastructure, data lineage systems, and metadata management for analytics platforms. Understanding of data governance and discoverability challenges.

Tech stack

Languages

ScalaJavaSQLPython

Frameworks

Apache FlinkApache SparkApache KafkagRPC

Databases

Cloud Data Warehouses (Snowflake/BigQuery/Redshift)Time-Series DatabasesMetadata & Catalog Systems

Tools

KubernetesApache Arrow/ParquetGit/GitHubMonitoring & Observability Tools (Prometheus/Grafana/DataDog)

Other

Cloud Platforms (AWS/GCP/Azure)CI/CD Pipelines & AutomationPerformance Profiling & BenchmarkingAI-Native Development Practices

Compensation

Pay and benefits.

Base·USD 250,000 – 350,000

Equity·Stock options

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.

Process

Interview steps.

  1. 01

    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. 02

    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. 03

    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. 04

    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. 05

    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. 06

    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. 07

    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. 08

    Offer & Negotiation

    Compensation discussion including base salary, equity package, and benefits. Opportunity to negotiate role scope, team structure, or strategic focus areas.

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.

As a Principal Engineer on the Data Platform team, you will be a technical anchor — setting direction, solving the hardest engineering problems, and elevating the entire team. You will work at the intersection of systems design, long-term architecture, and real-world engineering execution. In this specific role, you will lead the evolution of our declarative data pipelines, focusing on streaming ingestion and transformations.

What You'll Do

  • Drive the technical strategy and architecture for key Data Platform initiatives, focusing heavily on real-time data movement and incremental processing.

  • Lead design reviews and set engineering standards across teams.

  • Identify and resolve high-impact technical challenges and systemic bottlenecks to reduce latency and improve the efficiency of dynamic tables at cloud scale.

  • Mentor and grow senior engineers; raise the engineering bar.

  • Partner closely with product and infrastructure leadership on roadmap and direction.

  • Continuous hands-on technical deliverables in the most critical areas.

What We're Looking For

  • 14+ years of software engineering experience with deep expertise in distributed systems.

  • Demonstrated track record of defining and delivering platform-scale technical initiatives.

  • Expert-level knowledge of streaming and/or batch data systems (Flink, Spark, or equivalent), with specialized knowledge in incremental materialization algorithms.

  • Strong systems thinking — ability to reason across layers of complexity (infra, storage, compute, API).

  • A passion for engaging directly with customers to gain insight and inspiration

  • Experience influencing technical direction across organizations

  • Excellent written and verbal communication for technical and executive audiences.

Desirable

  • Experience with AI-augmented development practices and integrating LLM-based tooling into engineering workflows.

  • Familiarity with Snowflake platform internals or cloud-native data systems.

  • Experience with metadata systems, query optimization, or data catalog infrastructure.

  • Contributions to open source, such as top-level Apache projects

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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