Staff Software Engineer, Data Loading Infrastructure

Asana•San Francisco, CA

3d•$248,000 - $282,000•Hybrid

About The Position

As a Staff Software Engineer on Asana’s Data Loading Infrastructure team, you will lead the evolution of LunaDb, Asana’s core reactive data-loading platform. LunaDb powers Asana’s GraphQL-like query model and provides instantaneous updates across web, mobile, and external API platforms at a scale of billions of daily queries. You will drive stack modernization, challenge architectural assumptions, and build dependable, highly available distributed services. The role includes setting technical direction, improving workload isolation and query performance, and partnering with product engineering teams to keep the platform fast, reliable, and scalable as its capabilities expand. The position is based in Asana’s San Francisco office and follows an office-centric hybrid schedule. Standard in-office days are Monday, Tuesday, and Thursday. Most employees can work from home on Wednesdays; Friday arrangements depend on the work and partner teams. Recruiters can provide further details about in-office requirements. You will define and execute the technical roadmap; design, build, and operate distributed services, caching layers, and realtime data pipelines; and lead initiatives from architecture through safe migration, rollout, and ongoing production operations. You will also mentor teammates, guide cross-team architecture, participate in on-call rotations, lead incident investigations, and apply operational learnings to lasting improvements. The estimated base salary range is $248,000–$282,000. Actual base salary varies based on factors including market and objectively assessed individual qualifications. Compensation may also include equity, sales incentive pay for most sales roles, and benefits. Benefits vary by role, country, and local regulations.

Requirements

At least 7 years of software engineering experience designing, building, and operating large-scale distributed backend services.
At least 2 years of experience building and scaling high-throughput data pipelines, relational or non-relational data stores, and realtime streaming systems.
Proven track record 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.
Strong architectural judgment and ability to explain trade-offs clearly to engineering peers and cross-functional partners.
Practical expertise with Kubernetes, distributed caching technologies such as Redis, and cloud-native infrastructure design.
Curiosity about AI tools and emerging technologies, and willingness to learn and use them to enhance productivity, collaboration, or decision-making.

Responsibilities

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 and make 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 standards 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.