# Senior Software Engineer, Enterpirse Team
**Company:** [Snowflake](https://scaleengineer.com/companies/snowflake)
Senior Software Engineer, Enterprise Team at Observe by Snowflake - a leading AI-powered observability platform built on the Snowflake AI Data Cloud. You will design and own core features, APIs, and business logic for a high-performance system serving enterprise customers, handling hundreds of terabytes of telemetry daily. This role requires 5+ years of backend engineering experience with expertise in distributed systems, high-throughput/low-latency architecture, and strong proficiency in server-side languages like Go, Java, or Python.
**Role:** Backend Engineer
**Seniority:** Senior
**Locations:** CH-Zurich-Observe
**Salary:** 180000–250000 USD
[Apply](https://jobs.ashbyhq.com/snowflake/b29ce51b-a6b7-43af-81ce-3fe882913cc4)
Canonical: https://scaleengineer.com/jobs/snowflake/senior-software-engineer-enterpirse-team
---
## Responsibilities

- Design and Architect Core Platform Features: Lead the design and implementation of core features, APIs, and business logic powering Observe's high-performance observability platform. Take ownership of technical scoping and architectural decisions to ensure systems meet enterprise reliability, performance, and scalability standards while handling hundreds of terabytes of telemetry data.
- End-to-End System Ownership: Manage the complete software development lifecycle from technical requirements analysis and architecture design through implementation, testing, deployment, and production monitoring. Ensure solutions meet SLAs for enterprise customers and maintain operational excellence across the distributed platform.
- Cross-Functional Collaboration and Integration: Partner with product managers, infrastructure teams, data engineers, and SREs to design and deliver integrated solutions that enable rapid insights and troubleshooting capabilities. Coordinate with customer-facing teams to translate enterprise requirements into technical solutions that accelerate time-to-resolution.
- Production Incident Response and Optimization: Collaborate with SRE teams to diagnose, analyze, and resolve production issues at scale. Apply AI-assisted workflows and root-cause analysis tooling to accelerate incident resolution and implement preventative measures that improve platform reliability and observability.
- Engineering Excellence and Technical Leadership: Contribute to high engineering standards through thoughtful code reviews, architectural influence, and mentorship of junior engineers. Drive adoption of best practices in distributed systems design, testing strategies, and documentation that elevate team capabilities.
- AI-Native Problem Solving: Leverage AI-assisted workflows and LLM-integrated tools to enhance development velocity and problem-solving approaches. Explore emerging AI capabilities to discover more efficient solutions for complex observability challenges while maintaining a structured, experimental mindset.

## Requirements

### education

- {"name":"Computer Science or Engineering Degree","description":"Bachelor's degree (BS) or Master's degree (MS) in Computer Science, Computer Engineering, Software Engineering, or equivalent hands-on professional experience demonstrating core CS fundamentals."}

### technical

- {"name":"Server-Side Programming Languages","description":"Strong proficiency in one or more server-side languages including Go, Java, Scala, Python, Rust, or C++. Demonstrated ability to write clean, efficient, production-grade code following SOLID principles."}
- {"name":"Distributed Systems Architecture","description":"Deep understanding of distributed systems concepts including consensus algorithms, data replication, eventual consistency, load balancing, and horizontal scaling patterns used in high-throughput platforms."}
- {"name":"Data Infrastructure and Pipelines","description":"Practical knowledge of data ingestion, stream processing, time-series data handling, and analytics workloads. Understanding of columnar storage formats, data lakes, and efficient querying mechanisms at scale."}
- {"name":"Cloud Platforms and DevOps","description":"Hands-on experience with cloud infrastructure (AWS, GCP, Azure), containerization (Docker, Kubernetes), infrastructure-as-code, CI/CD pipelines, and observability tooling in production environments."}

### experience

- {"name":"Backend Systems Development","description":"5+ years of professional software engineering experience with substantial focus on backend application systems, distributed platforms, and microservices architecture."}
- {"name":"Large-Scale Systems Design","description":"Demonstrated track record designing and shipping production systems handling high throughput (petabyte-scale data ingestion), low latency requirements, and enterprise-grade reliability standards at scale."}
- {"name":"Performance and Reliability Engineering","description":"Proven experience optimizing system performance, implementing fault-tolerance mechanisms, and managing trade-offs between consistency, availability, and partition tolerance in distributed systems."}
- {"name":"Cross-Functional Collaboration","description":"Experience working in fast-moving, high-ownership environments collaborating across engineering, product, and infrastructure teams to deliver impactful, customer-facing solutions."}
- {"name":"Independent Problem Ownership","description":"Track record of taking end-to-end ownership of complex technical problems from initial scoping through delivery and production support, working independently without requiring constant direction."}

## Skills

### required

- {"name":"Go or Java","description":"Expert-level proficiency in Go (for systems programming, concurrency, and performance) or Java (for enterprise systems and ecosystem maturity). Ability to write idiomatic, high-performance code."}
- {"name":"Distributed Systems Design","description":"Strong grasp of distributed computing fundamentals, including fault tolerance, scalability patterns, data consistency models, and system design trade-offs relevant to observability platforms."}
- {"name":"System Architecture and Design","description":"Ability to design scalable, maintainable systems from requirements through implementation. Experience with API design, database schema optimization, and handling non-functional requirements like latency and throughput."}
- {"name":"Problem-Solving and Analytical Thinking","description":"Exceptional analytical skills with structured problem-solving approaches. Ability to diagnose complex issues, decompose problems into manageable components, and validate solutions empirically."}
- {"name":"Production Systems Ownership","description":"Proven ability to own production systems end-to-end including design decisions, implementation quality, testing rigor, deployment safety, and ongoing performance optimization."}

### preferred

- {"name":"Observability and Telemetry Platforms","description":"Experience building, deploying, or contributing to observability platforms, telemetry collection pipelines, distributed tracing systems, or log aggregation solutions at scale."}
- {"name":"OpenTelemetry, Prometheus, Jaeger","description":"Hands-on experience with industry-standard observability frameworks and tools including OpenTelemetry instrumentation, Prometheus metrics, Jaeger distributed tracing, or equivalent platforms."}
- {"name":"AI-Assisted Developer Tools","description":"Experience building or contributing to AI-assisted development tools, LLM-integrated workflows, or AI-powered automation systems that enhance developer productivity."}
- {"name":"SRE and Incident Response","description":"Background in Site Reliability Engineering practices, incident response automation, automated root-cause analysis tooling, or production troubleshooting at enterprise scale."}
- {"name":"Open-Source Contributions","description":"Active contributions to open-source projects in observability infrastructure, data platforms, developer tools, or adjacent domains demonstrating commitment to the broader engineering community."}
- {"name":"Apache Iceberg and Data Lakehouses","description":"Experience with modern data lakehouse architectures, Apache Iceberg table format, columnar storage optimization, or building systems on top of the Snowflake Data Cloud."}

## Tech stack

### tools

- {"name":"Docker and Kubernetes","description":"Container orchestration and deployment infrastructure for running distributed observability services and managing scalability across cloud environments."}
- {"name":"Prometheus","description":"Industry-standard metrics collection and monitoring system used both internally for platform monitoring and as a reference integration point."}
- {"name":"Jaeger","description":"Distributed tracing platform for visualizing and analyzing request flows across microservices, critical for understanding platform behavior and debugging."}
- {"name":"Git and CI/CD Systems","description":"Version control and continuous integration/deployment pipelines (GitHub, GitLab, Jenkins) for code quality, testing automation, and production deployment safety."}

### others

- {"name":"Distributed System Design Patterns","description":"Event sourcing, CQRS, eventual consistency models, and microservices patterns essential for building scalable observability infrastructure."}
- {"name":"AI and LLM Integration","description":"Integration of large language models and AI-assisted workflows for automating root-cause analysis, anomaly detection, and intelligent incident response capabilities."}
- {"name":"Cloud Infrastructure (AWS/GCP/Azure)","description":"Experience with cloud platforms for compute, storage, networking, and managed services that power scalable observability deployments."}
- {"name":"Observability Best Practices","description":"Understanding of modern observability principles including three pillars (logs, metrics, traces), context enrichment, and dashboarding for production visibility."}

### databases

- {"name":"Snowflake Data Cloud","description":"Native platform foundation providing scalable, cost-effective storage and query capabilities for processed telemetry data, logs, metrics, and traces at petabyte scale."}
- {"name":"Apache Iceberg","description":"Open table format used for efficient, ACID-compliant data lakehouse operations. Enables fast analytics and complex queries on stored observability data."}
- {"name":"ClickHouse","description":"Columnar time-series database commonly used in observability platforms for efficient aggregation and time-window queries on metrics and events."}
- {"name":"PostgreSQL","description":"Relational database used for transactional data, configuration state, and metadata management in the platform infrastructure."}

### languages

- {"name":"Go","description":"Primary language choice for systems programming, microservices, and performance-critical components at Observe. Preferred for its efficiency, concurrency model, and operational simplicity."}
- {"name":"Java","description":"Widely used for backend services, data processing pipelines, and enterprise platform components. Strong ecosystem for distributed systems and observability instrumentation."}
- {"name":"Python","description":"Used for data engineering, scripting, analytics, and integrations. Valuable for rapid prototyping and machine learning workflows in the platform."}
- {"name":"Scala","description":"Functional programming language with strong support for distributed computing frameworks and data engineering pipelines in the ecosystem."}

### frameworks

- {"name":"Spring Boot","description":"Enterprise Java framework for building microservices and RESTful APIs with production-grade observability and configuration management capabilities."}
- {"name":"gRPC","description":"High-performance RPC framework used for inter-service communication in distributed observability platforms, offering strong typing and efficient binary serialization."}
- {"name":"Apache Kafka","description":"Distributed event streaming platform for ingesting, buffering, and processing massive volumes of telemetry data in real-time across the platform."}
- {"name":"OpenTelemetry","description":"Standard instrumentation framework for traces, metrics, and logs. Core to how customer applications and internal systems emit observability signals."}

## Benefits

### benefits

- {"name":"Comprehensive Health Coverage","description":"Medical, dental, and vision insurance with competitive employer contributions across all US regions and international locations where applicable."}
- {"name":"Retirement and Financial Planning","description":"401(k) retirement plans with employer matching contributions and financial planning resources to support long-term wealth building."}
- {"name":"Generous Paid Time Off","description":"Competitive vacation, sick leave, and paid holidays. Flexible time-off policies encouraging work-life balance and personal wellness."}
- {"name":"Equity Compensation","description":"Stock options or RSUs as part of the total compensation package, allowing you to share in Snowflake's growth and success as a publicly traded company."}
- {"name":"Professional Development","description":"Education and training budget, conference attendance support, and learning resources to develop new skills and stay current with emerging technologies in observability and distributed systems."}
- {"name":"Remote-Flexible Work Environment","description":"Flexible work arrangements with option to work remotely or from Snowflake offices. Location flexibility to support diverse work preferences and lifestyles."}
- {"name":"Mental Health and Wellness","description":"Mental health support, counseling services, fitness programs, wellness initiatives, and resources supporting holistic employee well-being."}
- {"name":"Parental and Family Leave","description":"Generous parental leave policies, family planning support, and adoption assistance programs honoring diverse family structures."}

## Compensation

- **max:** 250000
- **min:** 180000
- **currency:** USD
- **stockOptions:** true

## Interview process

### steps

- {"name":"Initial Screening Call","description":"Conversation with a recruiter to discuss your background, experience with distributed systems and observability, career goals, and alignment with the role and team. Expect 30-45 minutes focused on your professional journey and initial technical interests."}
- {"name":"Technical Phone Screen","description":"In-depth discussion with a senior engineer covering your experience designing scalable systems, handling high-throughput data pipelines, and problem-solving approach. Expect systems design fundamentals, questions about your most impactful projects, and discussion of how you approach complex architectural decisions."}
- {"name":"Systems Design Interview","description":"Detailed system design exercise where you architect a large-scale observability or data platform component. You'll discuss trade-offs between consistency and availability, data storage strategies, API design, and scalability approaches. Expect 60-90 minutes with feedback and collaborative problem-solving."}
- {"name":"Behavioral and Technical Depth Interview","description":"Discussion of your experience collaborating across teams, taking ownership of complex projects, and handling production incidents. You'll discuss specific examples of challenges overcome, technical leadership moments, and how you approach learning new technologies and domains."}
- {"name":"Leadership Calibration Discussion","description":"Conversation with a director or senior leader about your vision for the observability space, thoughts on AI-assisted developer tools, and how you approach mentoring and raising team standards. Focuses on strategic thinking and cultural fit with Snowflake's AI-native mindset."}
- {"name":"Final Offer Discussion","description":"Conversation with hiring manager covering compensation, equity package, role expectations, team dynamics, and onboarding plans. Opportunity to ask questions about long-term career growth, technical direction, and working at Snowflake."}

## Full description
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.

Observe by Snowflake is an AI-powered observability platform built on the Snowflake AI Data Cloud and engineered for scale. We ingest and store logs, metrics, traces, and events on an open, scalable data lakehouse, using open formats like Apache Iceberg, at dramatically lower cost. A dynamic Context Graph and chat-based AI SRE provide rich context and automated workflows so teams can move from detection to root cause of production issue and resolution 10x faster.

Leading engineering teams at companies like Capital One, Topgolf, and Dialpad rely on Observe to troubleshoot hundreds of terabytes of telemetry daily while maintaining reliability at enterprise scale. As part of Snowflake, Observe combines startup-style ownership and velocity with the global reach, operational excellence, and ecosystem of one of the world’s leading data platforms.

## **The Team:**

We are hiring a Senior Software Engineer, Enterprise for our Engineering team at Observe by Snowflake. 

## **In this role your will:**

* Design, build, and own core features, APIs, and business logic powering a high-performance observability platform for enterprise customers
* Take end-to-end ownership from technical scoping and architecture through deployment, ensuring systems meet enterprise reliability and performance standards
* Collaborate with product, infrastructure, and data teams to deliver solutions that enable fast, actionable insights for engineering teams worldwide
* Partner with SREs and customer-facing teams to diagnose and resolve production issues, applying AI-assisted workflows to accelerate root-cause analysis
* Contribute to high engineering standards through thoughtful code review, mentorship, and architectural influence

## **Qualifications:**

* 5+ years of professional software engineering experience with a focus on backend application systems or distributed platforms
* Demonstrated experience designing and shipping production systems at scale, handling high throughput, low latency, and enterprise reliability requirements
* Strong proficiency in one or more server-side languages such as Go, Java, Scala, Python, or similar
* Ability to work independently and take ownership of complex technical problems from scoping through delivery, without waiting to be directed
* Experience collaborating across engineering, product, and infrastructure teams in a fast-moving, high-ownership environment
* Strong analytical thinking and structured problem-solving skills with a track record of shipping impactful, customer-facing work
* A BS/MS in Computer Science, Engineering, or equivalent experience

## **Bonus Points:**

* Experience with observability platforms, telemetry pipelines, or distributed tracing and logging systems (e.g., OpenTelemetry, Prometheus, Jaeger)
* Experience building or contributing to AI-assisted developer tools or LLM-integrated workflows
* Background in SRE practices, incident response automation, or root-cause analysis tooling
* Open-source contributions to observability, data infrastructure, or developer productivity 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](http://careers.snowflake.com)