Job description

SpaceX was founded under the belief that a future where humanity is out exploring the stars is fundamentally more exciting than one where we are not. Today, SpaceX is actively developing the technologies to make this possible, with the ultimate goal of making life multiplanetary and expanding consciousness to the stars. SpaceXSI is building Super Intelligence to help humanity understand the universe. Our teams are building the full Super Intelligence stack: from our Colossus supercomputers, to Grok models, to our suite of applications, including Grok Bot, Grok Build, Grok Imagine, Grok Voice, and X. We're creating a powerful flywheel where more compute trains better models, better models power more useful products, and what we learn from people using those products shapes what we build next. About the role The User Operations team owns the support experience for Cursor's users - from individual developers to our largest enterprise accounts. As we've scaled across regions, the volume and richness of our support data has grown faster than our ability to make sense of it. We're looking for a Data Analyst to change that. This role sits inside our Product and Engineering organization with a dotted line to the Head of User Operations and owns the data and reporting layer for Support. You'll turn ticket data, SLA performance, customer sentiment, and product signal into the dashboards and analysis that leadership uses to run the org - and into the evidence Product and Engineering use to decide what to fix next. Support is one of the clearest signals we have about where the product is working and where it isn't. Your job is to make that signal legible. What you'll do - Build and own the reporting layer for Support: ticket volume, SLA attainment, resolution times, help center performance, CSAT/CES/sentiment, and capacity utilization across regions and tiers - Partner with Support leadership to turn open questions - "are we getting faster but less accurate?", "where is enterprise pain actually concentrated?" - into analysis that drives decisions - Maintain the multi-signal model behind bug and issue prioritization, weighting frequency, breadth, support cost, and sentiment, so Engineering sees a defensible picture of what impacts users most - Design dashboards for two audiences: internal operational views for managers, and customer-facing views for enterprise accounts - Own data quality, governance, and reliability across Support data products, including our ticketing data and internal commitments - Surface Voice of Customer trends to Product, Engineering, and GTM, and help close the loop between what users report and what actually gets built You may be a fit if - You have 5+ years of experience in data analytics, analytics engineering, or a similar role - You have strong SQL skills - this is your primary toolkit - and you're comfortable building models and transformations (dbt or equivalent) - You've built reporting and dashboards in production that people actually depend on, not one-off charts - You can take a vague operational question and turn it into the right analysis without a playbook - You communicate clearly with both technical and non-technical stakeholders, and you're honest about what the data does and doesn't support - You're self-directed and comfortable owning ambiguous problems end to end

Requirements

Must-haves

Build and own the reporting layer for Support: ticket volume, SLA attainment, resolution times, help center performance, CSAT/CES/sentiment, and capacity utilization across regions and tiers
Partner with Support leadership to turn open questions - "are we getting faster but less accurate?", "where is enterprise pain actually concentrated?" - into analysis that drives decisions
Maintain the multi-signal model behind bug and issue prioritization, weighting frequency, breadth, support cost, and sentiment, so Engineering sees a defensible picture of what impacts users most
Design dashboards for two audiences: internal operational views for managers, and customer-facing views for enterprise accounts
Own data quality, governance, and reliability across Support data products, including our ticketing data and internal commitments
Surface Voice of Customer trends to Product, Engineering, and GTM, and help close the loop between what users report and what actually gets built
You may be a fit if
You have 5+ years of experience in data analytics, analytics engineering, or a similar role
You have strong SQL skills - this is your primary toolkit - and you're comfortable building models and transformations (dbt or equivalent)
You've built reporting and dashboards in production that people actually depend on, not one-off charts
You can take a vague operational question and turn it into the right analysis without a playbook
You communicate clearly with both technical and non-technical stakeholders, and you're honest about what the data does and doesn't support
You're self-directed and comfortable owning ambiguous problems end to end

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

sql

Platform: ashby
Effort: quick