Chime Financial, Inc
Senior Software Engineer, Data Engineering
San Francisco, CA, USA · Senior · Full-time
Stay score
odds of building a lasting career here
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
$1,131 more — $165,131 — moves this role to Level II and 2 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 $165,131 would place this position at wage Level II. 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
Green-card filing pattern in this occupation
Green-card follow-through: 100%
Files H-1B transfers
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 engineering team has been created keeping in mind the importance and criticality of data for the overall success of Chime.
- 5+ years experience transforming data to governed and lucid datasets
Responsibilities
- Additionally, you will have the unique opportunity to architect and build workflows that could potentially become de facto standards for the fintech industry.
- Design data schemas and scale them data for 10x data growth
- Ownership of all aspects of data - data quality, data governance, schema design, data quality and security
- Develop scalable data architecture and standardized data models that enable self-serve data insights using AI.
- 5+ years of hands-on experience to build and deploy production-quality data pipelines
- Own the ETL workflows and make sure the pipeline meets data quality and availability requirements
Requirements
- 5+ years of experience working with stakeholders to provide business insights
- 5+ years of experience writing SQL, Spark, AWS Glue, EMR, Airflow, Python
- To thrive in this role, you have
- Engineers are required to participate in on-call rotation.
Skills
- 3+ years of hands-on experience using any MPP database system like Snowflake, AWS Redshift or Teradata
- Track record of successful partnerships with Analytics, Data Science and DevOps teams
Compensation
- Below is the base salary offered for this role and level of experience.
- For commissioned roles, the base salary listed in this job description does not include incentive/variable pay.
- The actual base salary offered may be higher, depending on your location, skills, qualifications, and experience.
Benefits
- Full-time employees may also be eligible for bonus(es), competitive equity, and benefits.
Company info
- Wage Notice $164,000 - $227,000 USD A little about us At Chime, we believe that everyone can achieve financial progress.
- From day one, Chimers have worked tirelessly to out-hustle and out-execute competitors to bring our mission to life.
- Our culture remains deeply entrepreneurial, encouraging every Chimer to see themselves as stewards of our mission to help everyday Americans unlock their financial progress.
- We created Chime-a financial technology company, not a bank*-on the premise that core banking services should be helpful, easy, and free.
- The mission of this group is to build scalable data artifacts and insights that enable accurate, governed, data-driven decision-making..
This listing is sourced directly from Chime Financial, Inc's careers page and normalized into a canonical job model.