Jobs / United States / Natera INC

Natera INC

Senior Bioinformatics & Genomics Data System Engineer

San Carlos, CA; US Remote Posted today

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Skills this job asks for

LeadershipCompliancePythonAWSPostgreSQLMySQLLinuxGit

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Sponsorship verdict

Sponsorship possible

One solid signal, not two. Worth applying, and worth asking about sponsorship early.

  • Employer is on a government sponsor recordThe US Department of Labor certified 48 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first.
  • The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
  • No salary bar for this routeH-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area.
  • What Natera INC paid sponsored hires in similar roles4 certified filings for “Senior Data Science Production Engineer” (Data Scientists) in CA: $115k–$195k, median $144k.
  • Confirmed live todayWhen a source last listed this job as open.
Details and sources
Employer is on a government sponsor record
The US Department of Labor certified 48 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. Source: LCA disclosure data (US Department of Labor (OFLC)).
No salary bar for this route
H-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.
What Natera INC paid sponsored hires in similar roles
4 certified filings for “Senior Data Science Production Engineer” (Data Scientists) in CA: $115k–$195k, median $144k. Most were filed at wage level III (50%) — 3 lottery entries, ≈46% projected selection odds for cap-subject employers. Source: US Department of Labor LCA disclosure data (Oct 2025 – Jun 2026).

US H-1B: cap-subject employers enter a lottery weighted by wage level — Level I gets 1 entry, Level IV gets 4 (DHS projected selection odds ≈15% at Level I to ≈61% at Level IV). Universities and non-profit research employers are cap-exempt. The $100,000 fee for new petitions from abroad is currently blocked by a court order (appeal pending).

A verdict summarises public evidence. It is not legal advice and never a guarantee: the employer and the immigration authority decide. Sign in to factor in where you can already work.

About the role

As a Senior Bioinformatics & Genomics Data System Engineer of our Data Science Production Engineering (DSPE) department, you will be a key member in the DSPE DevOps team, to design, develop, test, deploy, maintain, and update DSPE's software tools, data platforms, cloud platforms, automation systems, and analytics systems. PRIMARY RESPONSIBILITIES: Technical • Ensure the timely and efficient delivery of software tools and systems with correct and robust functionality. • Contribute to key design, development, testing, deployment, validation, maintenance, and update activities for DSPE's software tools and data/cloud/automation systems. • Working with DSPE leadership teams, create suitable system architecture and infrastructure design documents that can be efficiently implemented and maintained. • Maintain and optimize software/system performance, by monitoring and studying different solutions' impacts on key system metrics, such as network I/O, disk I/O, RAM usage, CPU usage, disk space usage, etc. Quality, Compliance, and Documentation • Contribute to technical documentation's creation, maintenance, and updates for the DSPE Software Engineering & DevOps-team owned software tools and systems. • Create training materials, and contribute to training activities, for the DSPE Software Engineering & DevOps team-owned software tools and systems. Cross-Functional • Train and coach DSPE team members on new technologies, procedures, and guidelines/best practices. • Represent the DSPE Software Engineering & DevOps team in stakeholder meetings. QUALIFICATIONS: • Minimal Bachelor's Degree in Computer Science, Software Engineering, Bioinformatics, or a related field. Advanced degrees preferred. • Minimal 6 years of relevant industry experience for candidates with only a Bachelor's Degree. Minimal 3 years of relevant industry experience for candidates with a Master's Degree. Minimal 2 years of relevant industry experience for candidates with a Doctorate degree. • Minimal 3 years of working experience in a highly regulated environment, e.g., CLIA and/or FDA compliant settings. • Minimal 3 years of working experience in a Software Engineering, or a DevOps team. • Demonstrable experience in developing and maintaining custom-developed software tools or systems for production environments, preferable in high-throughput settings (e.g., heavy traffic and/or high computational load). • Demonstrable experience in creating software design specification documents, verification and validation documents, and user manuals. KNOWLEDGE, SKILLS, AND ABILITIES: • Excellent understanding of key bioinformatics and genomics concepts, and NGS technologies. • Excellent Python programming skills, with demonstrable bioinformatics or genomics application and/or automation system development experience. • Excellent understanding of AWS services relevant to bioinformatics and genomics applications. • Working experience with key AWS services, such as Batch, ECS, S3, EC2, HealthOmics, etc., preferably in developing for-production software tools/systems. • Proficient with RDBMS systems such as PostgreSQL and/or MySQL, and demonstrable working experience in for-production database-based application development. • Working experience with bioinformatics and genomics-specific file types, such as BCL, FASTQ, BAM, VCF files. • Working knowledge in optimizing system architecture and individual components for performance, scalability, and/or reliability, especially for genomics-scale data. • Working knowledge in tool/system performance evaluation methods, and familiar with the key factors, such as RAM, Disk IO, Network IO's impact on system/tool's performance, especially for bioinformatics and genomics applications. • Working knowledge in SDLC and software

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