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Staff Software Engineer, Data Loading Infrastructure

Asana San FranciscoUSD 248,000–282,000 / yearLead

Key requirements

  • Kubernetes
  • Graphql
LunaDb is Asana’s core reactive data loading platform, powering our GraphQL-like query model to deliver instantaneous updates across web, mobile, and external API platforms at a scale of billions of daily queries. As a Staff Software Engineer on the Data Loading Infrastructure team, you will lead the next chapter of LunaDb by driving stack modernization, challenging architectural assumptions, and building dependable, highly available distributed services. You will set technical direction, improve workload isolation and query performance, and partner closely with product engineering teams to ensure Asana remains fast, reliable, and scalable as we expand platform capabilities. This role is based in our San Francisco office with an office-centric hybrid schedule. The standard in-office days are Monday, Tuesday, and Thursday. Most Asanas have the option to work from home on Wednesdays. Working from home on Fridays depends on the type of work you do and the teams with which you partner. If you're interviewing for this role, your recruiter will share more about the in-office requirements. What you’ll achieve Define and execute a technical roadmap that improves scalability, reliability, developer productivity, and operational simplicity. Design, build, and operate highly available distributed services, caching layers, and realtime data pipelines processing millions of events per second. Advance query performance, cache invalidation, workload isolation, and resource efficiency while preserving data correctness across the platform. Partner with product engineers to support new capabilities, making complex data access easier, faster, and more predictable. Lead major initiatives through architecture, implementation, safe migration, rollout, and long-term production operations. Mentor teammates, guide cross-team technical architecture, and raise the bar for system design, reliability, and engineering quality. Participate in on-call rotations, lead incident investigations, and translate operational learnings into lasting improvements across tooling, automation, and infrastructure architecture. About you 7+ years of software engineering experience designing, building, and operating large-scale distributed backend services. 2+ years of experience building and scaling high-throughput data pipelines, relational/non-relational data stores, and realtime streaming systems. Proven track record of operating mission-critical production systems and maintaining high reliability standards. Demonstrated technical leadership in setting architectural direction, driving cross-team consensus, and mentoring senior engineers. Deep architectural judgment with the ability to articulate trade-offs clearly to both engineering peers and cross-functional partners. Practical expertise with Kubernetes, distributed caching technologies (such as Redis), and cloud-native infrastructure design. Demonstrates curiosity about AI tools and emerging technologies, with a willingness to learn and leverage them to enhance productivity, collaboration, or decision-making At Asana, we're committed to building teams that include a variety of backgrounds, perspectives, and skills, as this is critical to helping us achieve our mission. If you're interested in this role and don't meet every listed requirement, we still encourage you to apply. What we’ll offer Our comprehensive compensation package plays a big part in how we recognize you for the impact you have on our path to achieving our mission. We believe that compensation should be reflective of the value you create relative to the market value of your role. To ensure pay is fair and not impacted by biases, we're committed to looking at market value which is why we check ourselves and conduct a yearly pay equity audit. For this role, the estimated base salary range is between $248,000 - $282,000. The actual base salary will vary based on various factors, including market and ind

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