DoorDash

DoorDash

Software Engineer, Data Platform

US · Mid

Sponsorship not specified$131k-$192kDetected 6 days ago
CassandraKafkaMachine LearningSparkAirflowData AnalysisLogistics

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odds of building a lasting career here

64Sponsors, lottery-bound
Cap-exempt (no lottery)0
Sponsors this role100
Entry-level history0
PERM / green-card track0
Lottery odds (Level IV)94
Fits your clock70

Sponsors, but it's cap-subject — you still face the weighted lottery (~61% per draw at Level IV). Good if you win; have a cap-exempt backup on your list.

Lottery odds assume a STEM candidate.

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Employer immigration record

from this employer's Department of Labor filings

Green-card filing pattern in this occupation

Context, not a finding about this posting: of this employer's 73 green-card filings in this occupation, 100% were for a worker who already held the job.

Green-card follow-through: 53%

Of 34 labor certifications old enough to have been used, 16 expired without the employer filing the next step. Median time from filing to decision: 481 days.100% of their filings were for a worker who already held the job.Only certifications past the 180-day window are counted — recent ones cannot have expired yet.

Files H-1B transfers

125 transfer filings in the last year, covering 125 workers. Median labor-condition decision: 7 days. An employer that already files transfers is one that can take over an existing H-1B.

Sourced from Department of Labor LCA, PERM and prevailing-wage disclosure data. Employer matching is by name, so figures may be split across an employer's legal entities. Absence of a filing means none appears in our copy of the data, not that none exists.

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About the role

  • The Data Platform team spans data mobility frameworks, ingestion, infrastructure, tools, and governance.
  • In parallel, these teams establish strong data quality, cataloging, privacy, and compliance standards to ensure trust in analytics and regulatory adherence.
  • As relatively high-impact teams, they offer engineers the opportunity to shape the roadmap, influence core platform decisions, and directly enable DoorDash's business-critical insights and real-time personalization capabilities.

Responsibilities

  • DoorDash is a data driven organization and relies on timely, accurate and reliable data to drive many business and product decisions.
  • Collaborate with stakeholders building solutions on top of the platform

Requirements

  • You must be located in San Francisco, CA, Sunnyvale, CA, Seattle, WA, or New York, NY.
  • We're excited about you because you have…
  • Proficiency in using AI coding tools (e.g., Claude Code, Codex, Cursor) in the full software development lifecycle, including designing, generating code, testing, monitoring and releasing software

Nice to have

  • Prior technical experience in Big Data infrastructure & governance - you've built meaningful pieces of data infrastructure.

Compensation

  • The successful candidate's starting pay will fall within the pay range listed below and is determined based on job-related factors including, but not limited to, skills, experience, qualifications, work location, and market conditions.
  • Base salary is localized according to an employee's work location.
  • In addition to base salary, the compensation for this role includes opportunities for equity grants.
  • flexible paid time off/vacation, plus 80 hours of paid sick time per year.
  • For hourly roles:

Benefits

  • In addition to base salary, the compensation for this role includes opportunities for equity grants.
  • DoorDash also offers medical, dental, and vision benefits, 11 paid holidays, disability and basic life insurance, family-forming assistance, and a mental health program, among others.
  • To learn more about our benefits, visit our careers page here.
  • See below for paid time off details:

Company info

  • The Core Data Platform organization owns all the infrastructure necessary to run an operationally efficient analytical data stack.

This listing is sourced directly from DoorDash's careers page and normalized into a canonical job model.