Apptad

Apptad-Data Engineering Tech Lead

South San Francisco, San Mateo County

Sponsorship not specifiedDetected 142 days ago

PythonSQLRedshiftAWSAirflowData EngineeringEHR/EMR

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odds of building a lasting career here

37Risky

Cap-exempt (no lottery)0

Sponsors this role80

Entry-level history0

PERM / green-card track0

Lottery odds40

Fits your clock70

Thin sponsorship signal and lottery-bound. A low-probability bet with your clock running. Prioritize cap-exempt roles and proven entry-level sponsors first.

Lottery odds assume a STEM candidate.

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Employer immigration record

from this employer's Department of Labor filings

Third-party placement is common here

27% of this employer's visa filings place the worker at a client company rather than at the employer itself, across 6 clients. Your visa, salary band and layoff exposure would follow the employer of record, not the client.Most common: Cigna HealthCare · Bank of New York Mellon · Bayer Crop ScienceFiles as an H-1B dependent employer.

Files H-1B transfers

11 transfer filings in the last year, covering 11 workers. Median labor-condition decision: 310 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

Job Title: Data Engineering Tech Lead Job Location: South San Francisco, CA 3 Days Onsite Job Duration: Long Term Qualification & Skills Required: 10 years of experience in Data Engineering, Integrations, Data Modeling, Data Profiling, Data Quality, Orchestration Hands on expert experience in the AWS Data Engineering Tech Stack: S3, Glue, Airflow, SQL,
Python, PySpark, Lambda, RDS, Redshift, EMR, and API Gateway Detailed experience with data modeling and data integration (ETL/ELT) Data Product …

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