Astronomer

Astronomer

Data Platform Engineer

San Francisco · Mid

Sponsorship not specified$200k-$250kDetected 98 days ago
PythonGitSnowflakeDatabricksPlatform EngineeringAirflowData EngineeringAI OrchestrationCommunication

Stay score

odds of building a lasting career here

59Sponsors, lottery-bound
Cap-exempt (no lottery)0
Sponsors this role80
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$137,0931 entry
Level II$165,1312 entries
Level III$193,1493 entries
Level IV$221,1874 entries

$21,187 more — $221,187 — 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 $221,187 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) · San Francisco-Oakland-Fremont, CA. 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

Files H-1B transfers

1 transfer filing in the last year, covering 1 worker. 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

  • You'll have the chance to work with cutting-edge technology, help customers solve complex data challenges, and influence our product's evolution through client feedback.
  • This role is ideal for someone who wants to make a visible impact while growing into an expert in workflow orchestration and Apache Airflow.
  • Be a Trusted Advisor: Conduct demos and provide technical guidance to engineering teams, showing them how our platform can transform their workflows.

Responsibilities

  • Become an expert in Airflow, workflow orchestration, and the data engineering landscape as you collaborate across departments and work on impactful projects.
  • Drive Community Impact: Contribute to the Apache Airflow community by creating technical content and best practices, positioning Astronomer as a thought leader in workflow orchestration.
  • Develop and Grow: Become an expert in Airflow, workflow orchestration, and the data engineering landscape as you collaborate across departments and work on impactful projects.

Requirements

  • Familiarity with core data engineering concepts including orchestration, ELT, Git, and Role-Based Access Control (RBAC), with hands-on experience or working knowledge of Apache Airflow in a customer environment.
  • Experience with open-source data tools.
  • Data Engineering Know-How: Familiarity with core data engineering concepts including orchestration, ELT, Git, and Role-Based Access Control (RBAC), with hands-on experience or working knowledge of Apache Airflow in a customer environment.
  • Experience and Expertise: 2+ years in a Sales Engineering, Solutions Engineering, Consulting or similar role within the data space, ideally with experience in modern data tools like Snowflake, Databricks, Fivetran, or Tableau.
  • Curiosity and Customer Empathy: A genuine desire to understand customer needs, patience, and empathy to support them through challenges.
  • Drive to Innovate: Eagerness to learn and experiment with new technical concepts, tools, and approaches to stay ahead in the data industry.
  • Background in designing data workflows in a production environment.
  • Customer-facing experience in a technical or consultative role.
  • Experience working with Command Line Interfaces (CLI).
  • The estimated total compensation for this role ranges from $200,000 - $250,000, along with an equity component. This range is merely an estimate, and the width of the range reflects willingness to consider candidates with broad prior seniority. Actual compensation may deviate from this range based on skills, experience, and qualifications.
  • #LI-Remote

Skills

  • Effective Communication: Strong verbal and written communication skills to simplify complex technical concepts for diverse audiences.
  • Hands-on Python scripting skills for data pipeline support.
  • Actual compensation may deviate from this range based on skills, experience, and qualifications.

Compensation

  • The estimated total compensation for this role ranges from $200,000 - $250,000, along with an equity component.

Benefits

  • The estimated total compensation for this role ranges from $200,000 - $250,000, along with an equity component.

Company info

  • Astronomer empowers data teams to bring mission-critical software, analytics, and AI to life and is the company behind Astro, the industry-leading unified DataOps platform powered by Apache Airflow®.
  • Astro accelerates building reliable data products that unlock insights, unleash AI value, and powers data-driven applications.
  • Trusted by more than 800 of the world's leading enterprises, Astronomer lets businesses do more with their data.
  • To learn more, visit www.astronomer.io http://www.astronomer.io.
  • We are an equal opportunity employer: we do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
  • Solve Real-World Problems: Design and implement proof-of-concept solutions that help customers tackle real data challenges, from concept to production.

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