Jobs / United States / Doordash INC
Data Insights and Tooling Enablement Program Lead
Doordash INC · 🇺🇸 Chicago, IL; Minneapolis, MN; Nashville, TN; Milwaukee, WI; Austin, TX; Indianapolis, IN; Detroit, MI; Atlanta, GA; Miami, FL; Charlotte, NC; Philadelphia, PA; Cincinnati, OH; Richmond, VA
Sponsorship verdict
Sponsorship possible
One solid signal, not two — worth applying, and worth asking about sponsorship early.
- Employer is on a government sponsor recordThe US Department of Labor certified 396 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 147 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
- The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
- No salary bar for this routeH-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.
- What Doordash INC paid sponsored hires in similar roles15 certified filings for “Software Engineer, Machine Learning” (Data Scientists) in CA: $169k–$217k, median $188k. Most were filed at wage level II (43%) — 2 lottery entries, ≈31% projected selection odds for cap-subject employers. Source: US Department of Labor LCA disclosure data (Oct 2025 – Jun 2026).
- Confirmed live todayWhen a source last listed this job as open.
US H-1B: cap-subject employers enter a lottery weighted by wage level — Level I gets 1 entry, Level IV gets 4 (DHS projected selection odds ≈15% at Level I to ≈61% at Level IV). Universities and non-profit research employers are cap-exempt. The $100,000 fee for new petitions from abroad is currently blocked by a court order (appeal pending).
A verdict summarises public evidence; it is not legal advice and never a guarantee — the employer and the immigration authority decide. Sign in to factor in where you can already work.
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Sponsor Radar — Doordash INC
The US Department of Labor certified 396 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 147 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
Past sponsorship or register membership never guarantees sponsorship for this vacancy or for you. Full Sponsor Radar for Doordash INC →
About the role
About the Team The Talent Acquisition Operations (TA Ops) team is transforming into a strategic partner, driving global recruiting efficiency and scalability. We focus on optimizing processes, implementing technology, and leveraging data to align talent acquisition with DoorDash's and Wolt's evolving business needs. Our mission is to empower recruiters with streamlined operations and data-driven insights, ensuring we attract and retain top talent globally. About the Role As a Data Insights and Tooling Enablement Program Lead, you will be instrumental in leveraging data and optimizing our TA tech stack to provide actionable insights and enhance recruiter effectiveness globally. In your first 90 days, you'll focus on auditing our current data sources and tooling capabilities, identifying key pain points, and partnering with stakeholders to define critical reporting and enablement needs. Success in this role will be measured by improved data accessibility, enhanced recruiter efficiency through optimized tools, and the consistent delivery of high-quality, actionable insights. This role offers the opportunity to drive significant impact by transforming our global talent acquisition strategy through data-driven decisions and effective tool utilization. You will report into the Senior Manager of Recruitment Strategy and Operations on our TAOps team in our People and Culture organization. You’re excited about this opportunity because you will… • Design and implement robust data solutions to provide actionable insights into talent acquisition performance, trends, and opportunities. • Partner with People Analytics and IT teams to integrate various data sources (ATS, CRM, HRIS, etc.) for a holistic view of the talent pipeline, providing dashboards and reporting.. • Identify and recommend opportunities for tooling optimization within our TA tech stack (e.g., ATS, CRM, assessment tools), ensuring they meet business needs and enhance recruiter productivity. • Lead the evaluation, implementation, and adoption of new TA technologies that improve efficiency, candidate experience, and data capture. • Develop and deliver training programs and resources to empower recruiters and TA professionals to effectively leverage data insights and utilize recruiting tools. • Conduct in-depth analysis of recruiting metrics, identifying root causes for performance fluctuations and recommending strategic adjustments. • Support data governance initiatives to ensure data integrity, privacy, and compliance across all TA systems. We’re excited about you because… • You have a minimum of 3-5 years of experience in data analysis, business intelligence, or tooling enablement, ideally within talent acquisition or HR operations. • You possess a proven track record of translating complex data into clear, actionable insights and influencing decision-making. • You demonstrate strong analytical and problem-solving skills • You have extensive experience with Applicant Tracking Systems (ATS) , Candidate Relationship Management (CRM) systems , and other recruiting technologies (e.g., Greenhouse, Workday, Beamery, Eightfold, Gem). • You have experience in project managing technology implementations and driving user adoption. • You have excellent communication and interpersonal skills , with the ability to explain technical concepts to non-technical audiences and build strong stakeholder relationships. • You are passionate about leveraging technology and data to solve complex business problems and enhance operational efficiency. 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