Databricks

Databricks

Solutions Architect - Communications, Media, Entertainment and Games

Remote - New York · Senior

Sponsorship not specified$180k-$248kDetected 5 days ago
PythonSQLSnowflakeDatabricksAWSGCPAzureMachine LearningData EngineeringUnityCommunication

Stay score

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.

Personalize to your clock →

H-1B wage level

the lottery is wage-weighted — each level is one more entry

Level III · 3×
Level I$109,8451 entry
Level II$137,7172 entries
Level III$165,5893 entries
Level IV$193,4614 entries

$13,461 more$193,461 — moves this role to Level IV and 4 lottery entries. That figure is inside the range the employer already advertised.

Based on the DOL prevailing wage for this occupation and worksite, a base salary of $193,461 would place this position at wage Level IV. That figure is within the posted range, and I'd like to target it. This role classifies under "Software Developers" for prevailing-wage purposes.

DOL prevailing wage, 2026-27 wage year · Software Developers (15-1252) · New York-Newark-Jersey City, NY-NJ. Wage level is derived by USCIS from the offered wage, occupation and worksite; the occupation shown is inferred from the job title.

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 72 green-card filings in this occupation, 99% were for a worker who already held the job.

Green-card intent detected

Databricks, Inc. obtained a prevailing wage determination for Sales Engineers in San Francisco, CALIFORNIA on 2026-06-15. No matching green-card filing appears in our data yet. The determination expires in 5 days (2026-09-12), and a green-card filing must follow before then or the employer starts over.+2 more active determinations on file

Green-card follow-through: 52%

Of 52 labor certifications old enough to have been used, 25 expired without the employer filing the next step. Median time from filing to decision: 482 days.99% 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

163 transfer filings in the last year, covering 1450 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.

Community outcomes

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About the role

  • The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles.
  • For more information regarding which range your location is in visit our page here.

Requirements

  • 6+ years in solutions architecture, data engineering, technical pre-sales, or a senior hands-on technical role
  • Strong coding proficiency in Python and SQL - you must demonstrate live coding, debugging, and solution-building skills
  • Proficient on the Databricks Platform (or demonstrated ability to achieve proficiency rapidly) with a developing technical specialization in one area (e.g., real-time/streaming, ML/AI, data governance, migrations)
  • Experience with production deployments on public cloud (AWS, Azure, or GCP), including infrastructure, security, and governance considerations
  • Track record of driving platform adoption and consumption growth within accounts
  • Bachelor's or Master's degree in Computer Science, Engineering, or a quantitative discipline (or equivalent experience)

Nice to have

  • Databricks certifications (Data Engineer, ML, Platform)
  • Experience with competitive platforms (Snowflake, AWS native services, Azure Synapse) - understanding the landscape you'll position against
  • Background in a data/AI company or cloud provider
  • Presentation → Reference Check
  • Databricks is committed to fair and equitable compensation practices.
  • Based on the factors above, Databricks anticipates utilizing the full width of the range.
  • About Databricks
  • Databricks is the Data and AI company.

Compensation

  • Databricks is committed to fair and equitable compensation practices.
  • The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles.
  • Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location.
  • The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above.
  • Zone 1 Pay Range
  • $180,000 - $247,500 USD

Benefits

  • At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees.
  • For specific details on the benefits offered in your region click here.

Company info

  • You combine deep technical expertise with strategic thinking to position Databricks as the foundation of your customers' data and AI strategy.
  • Our Commitment to Diversity and Inclusion At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel.
  • At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel.

Equal opportunity

  • Our Commitment to Diversity and Inclusion

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