MongoDB

MongoDB

Manager, Technical Services

Austin

Sponsorship not specified$133k-$261kDetected 4 days ago
Distributed SystemsNoSQLMongoDBAWSGCPData VisualizationPerformance ManagementCustomer SupportLeadershipCommunication

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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 29 green-card filings in this occupation, 97% were for a worker who already held the job.

Green-card intent detected

MONGODB, INC. obtained a prevailing wage determination for Software Developers in San Francisco, CALIFORNIA on 2026-06-29. No matching green-card filing appears in our data yet. The determination expires in 21 days (2026-09-26), and a green-card filing must follow before then or the employer starts over.

Green-card follow-through: 59%

Of 17 labor certifications old enough to have been used, 7 expired without the employer filing the next step. Median time from filing to decision: 495 days.97% 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

16 transfer filings in the last year, covering 16 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 team has offices in New York City, Toronto, Austin, Palo Alto, Vancouver, Sydney, Gurgaon (India), Tel Aviv, Dublin, and Buenos Aires.
  • Individuals in this team are experts in addressing issues related to MongoDB's database functions to enable successful Fedramp customer implementations.
  • Click here to learn more about our Technical Services team.

Responsibilities

  • Advising on design and architecture including global distribution and replication of data to support high availability, low latency and meeting data sovereignty requirements
  • Advising on upcoming roadmap features and advocating for the customer in articulating business cases to drive issue resolution
  • Working on named accounts to build rapport and an in-depth understanding of customer architecture and environment(s) while encouraging expansion of use
  • Strong people management skills with a track record of building and managing individuals with a strong focus on customer experience and technical excellence
  • Ability to lead-by-example with strong diagnostic and troubleshooting skills

Compensation

  • Salary is one part of MongoDB's total compensation and benefits package.
  • Please note, the base salary range listed below and the benefits in this paragraph are only applicable to U.S.-based candidates.
  • MongoDB's base salary range for this role in the U.S. is:

Benefits

  • Continuously learning and growing skills via participation in training, maintaining industry awareness and development of training to share subject matter expertise more broadly across the team

Company info

  • Technical Services has nearly 200 global team members in offices spanning the entire globe.
  • We are looking for candidates who are comfortable working a Wednesday - Sunday or Saturday - Wednesday schedule.
  • We're looking to speak with candidates based on the east coast and able to work EST 1st shift hours.

Visa & Work Authorization

  • citizen, U
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This listing is sourced directly from MongoDB's careers page and normalized into a canonical job model.