Data Engineer, Analytics
Discord - San Francisco Bay Area
Posted Jan 14, 2026
Benefits
- Parental leave
- Not verified
- Non-birth-parent leave
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- Family-building benefits
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- Fertility benefits: Not verified
- Adoption assistance: Not verified
- Surrogacy assistance: Not verified
- Mental health support
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- Relocation assistance
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- Childcare support
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- Learning budget
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- Verification
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- Salary
- Not verified not verified - source not recorded; timestamp not recorded
- 401(k) match
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Schedule
- Shift type
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- Weekend work
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Application
- Cover letter
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- Assessment
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- Deadline
- Not stated
Where they hire
State eligibility is not yet verified.
About this role
Data Engineer, Analytics San Francisco Bay Area Discord is used by over 200 million people every month for many different reasons, but there's one thing that nearly everyone does on our platform: play video games. Over 90% of our users play games, spending a combined 1.5 billion hours playing thousands of unique titles on Discord each month. Discord plays a uniquely important role in the future of gaming. We are focused on making it easier and more fun for people to talk and hang out before, during, and after playing games. Discord is looking for an experienced and passionate Data Engineer, Analytics to join our data team! You will be owning the transformation and semantic layer that turns data into clean, tested, well-documented tables and dashboards that data scientists, product managers, and business stakeholders can trust and self-serve from. You'll define and operationalize the metrics that inform how we identify opportunities, measure success, and make decisions. If this sounds exciting to you and you're passionate about data modeling, metric design, and empowering teams to move faster with reliable data, read on! We're hiring for multiple verticals on our Data Engineering team, including Growth and Safety. What you will be doing : - Design, build, and maintain curated analytical datasets and data models that serve as the canonical sources for metrics, dashboards, and analyses. - Partner closely with data science, product managers, and engineering teams to translate business questions into well-modeled, performant, and discoverable data assets. - Execute metric workflows, from
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