Senior Staff Data Engineer Visa Sponsorship Jobs in California
Senior staff data engineer roles in California attract strong visa sponsorship activity, particularly from technology companies in the San Francisco Bay Area, Los Angeles, and San Diego. Employers like Google, Meta, Apple, and Databricks regularly hire at this level. California's concentration of data-intensive industries makes it one of the most active states for senior staff data engineer hiring.
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About The Role
We're looking for a Senior Staff Data Engineer to be the technical backbone of our Data & ML Platform team — the foundation powering analytics, product experiences, and machine learning across Hinge Health. This is a high-ownership IC role for someone who wants to set the technical vision for the platform, drive architecture across organizational boundaries, and shape how Hinge Health builds on data and ML for years to come. Your scope extends beyond any single team or system. You'll own the most consequential architectural decisions across the data platform — how streaming and batch systems converge, how data models serve both analytical and ML workloads, and how the platform evolves as the company's AI ambitions scale. You'll work in a modern stack including Python, SQL, Spark, dbt, Kafka, Flink, Databricks, and AWS, and increasingly at the boundary where data platform meets ML platform — feature pipelines, serving layers, and the infrastructure that makes ML models production-ready. This is not a role where you go deep on a single system. You'll operate across the full platform surface — identifying the highest-leverage technical problems the organization faces, driving alignment across engineering, Data Science, and product teams, and making architectural decisions that others build on. You should be equally comfortable authoring a platform-wide technical strategy, debugging a production incident, mentoring senior engineers, and explaining tradeoffs to leadership.
What You'll Accomplish
- Set the technical vision for the data platform: Own the long-term architectural direction for how streaming and batch systems, data models, and serving layers fit together. Make the architectural decisions that other teams and engineers build on — balancing reliability, performance, cost, and long-term maintainability across the platform.
- Build at the intersection of data and ML platform: Design the infrastructure that connects the data platform to ML workloads — feature pipelines, feature stores, and serving layers. Partner with Data Science to ensure the data platform produces ML-ready data and supports model training and inference workflows reliably.
- Raise the engineering bar across the organization: Set standards that extend beyond your immediate team — data modeling patterns, schema governance, testing practices, pipeline reliability, and code quality. Mentor senior engineers, influence engineering culture, and be the technical authority the broader R&D organization looks to on data platform decisions.
- Drive cross-organizational technical initiatives: Lead complex initiatives that span multiple teams, services, and domains. Define data contracts with upstream services, drive schema evolution strategies, and resolve systemic technical friction between data producers and consumers across the company.
- Own platform reliability and operational excellence: Drive the reliability posture of the most critical data systems. Lead improvements in observability, data quality, incident response, and cost efficiency at a platform level — making the data foundation trustworthy enough that every team in the organization can build confidently on top of it.
Basic Qualifications
- Bachelor’s Degree (or equivalent) in Computer Science, Engineering, or a related technical field.
- 10+ years of hands-on data engineering experience, with a significant portion spent in platform or infrastructure roles building systems that other teams depend on.
- Experience architecting data systems across batch and streaming paradigms, including technologies such as Kafka, Flink, Spark, or equivalent.
- Strong proficiency in Python and SQL, with deep experience in distributed data processing frameworks and data platform design.
- Data and ML platform crossover: You've built or contributed to ML platform infrastructure — feature pipelines, feature stores, model serving, or MLOps tooling — as a natural extension of your data engineering work. You understand the ML lifecycle well enough to design data systems that serve it effectively.
- Track record of setting technical direction across an organization — driving alignment across multiple teams, making architectural decisions with broad impact, and delivering outcomes without formal authority.
- Demonstrated experience mentoring senior engineers and influencing engineering culture and standards beyond your immediate team.
Preferred Qualifications
- Built in a growth-stage environment: Your strongest work was at a mid-sized or scaling company where you had to make foundational architectural decisions — not at a large tech company where the platform was already built.
- Deep data modeling and governance instincts: You care about schema design, data contracts, and data quality as much as you care about pipeline throughput. You've driven improvements in how upstream services produce data and how downstream teams consume it.
- Product and business awareness: You connect your technical work to the problems the business is trying to solve. You understand the product use cases your platform enables and use that context to prioritize and make better architectural choices.
- Operational rigor in regulated environments: You value SLOs, incident management, and observability as first-class concerns. Experience in HIPAA, SOC 2, or similarly regulated environments is a plus.
- Experience with Databricks ecosystem: Delta Lake, MLflow, Unity Catalog — familiarity with this stack accelerates your impact.
- AI-forward engineering practices: You actively use AI-assisted development tools and see them as a force multiplier for both your own productivity and the team's.
Hinge Health Hybrid Model
This is a hybrid role based in the San Francisco office, requiring in-person attendance three days per week for a full 8-hour business day. On remote days, employees are expected to work during core business hours with flexibility. The office is part of a dog-friendly workplace program, and while travel is not regularly required, occasional off-site/on-site events may occur. Physical demands are minimal and primarily involve standard office activities such as sitting, typing, and video conferencing.
About Hinge Health
At Hinge Health, we’re using technology to scale and automate the delivery of healthcare – starting with musculoskeletal (MSK) conditions, which affect over 1.7 billion people worldwide. With an AI-powered human-centered care model, Hinge Health leverages cutting-edge technology to improve outcomes, experiences and costs to help people move beyond their pain. The platform addresses a broad spectrum of MSK care – from acute injury, to chronic pain, to post-surgical rehabilitation – through personalized, evidence-based care. As the preferred partner to 50+ health plans, PBMs and other ecosystem partners, Hinge Health is available to over 20 million people across more than 2,550 employers. The company is headquartered in San Francisco with additional offices in Montreal and Bangalore.
What You'll Love About Us
- Inclusive healthcare and benefits: On top of comprehensive medical, dental, and vision coverage, we offer employees and their family members help with gender-affirming care, tools for family and fertility planning, and travel reimbursements if healthcare isn’t available where you live.
- Planning for the future: Start saving for the future with our traditional or Roth 401k retirement plan options which include a 2% company match.
- Modern life stipends: Manage your own learning and development. Grow with us through discounted company stock through our ESPP with easy payroll deductions.
Hinge Health is an equal opportunity employer and prohibits discrimination and harassment of any kind. We make employment decisions without regards to race, color, religion, sex, sexual orientation, gender identity, national origin, age, veteran status, disability status, pregnancy, or any other basis protected by federal, state or local law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. We provide reasonable accommodations for candidates with disabilities. If you feel you need assistance or an accommodation due to a disability, let us know by reaching out to your recruiter. By submitting your application you are acknowledging we are using your personal data as outlined in the personnel and candidate privacy policy.
Beware of Phishing Attempts: We've noticed an increase in phishing where fraudsters impersonate employees and send fake job offers to steal sensitive information. We'll never ask for financial details during the hiring process and only use "@hingehealth.com" emails. If you receive a suspicious offer, stop communication and report it to the US FBI Internet Crime Complaint Center. To verify an email from our recruiting team, forward it to security@hingehealth.com.
Compensation Range
$240K - $360K
Senior Staff Data Engineer Job Roles in California
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Search Senior Staff Data Engineer Jobs in CaliforniaSenior Staff Data Engineer Jobs in California: Frequently Asked Questions
Which companies sponsor visas for senior staff data engineers in California?
Large technology employers are the most consistent sponsors for senior staff data engineer roles in California. Companies like Google, Meta, Apple, Salesforce, Adobe, Databricks, and Snap have established immigration programs and regularly file H-1B visa petitions for senior engineering positions. Enterprise technology and cloud infrastructure firms tend to have dedicated immigration counsel and structured sponsorship processes for roles at this seniority level.
Which visa types are most common for senior staff data engineers in California?
The H-1B is the most common visa for senior staff data engineers in California, as the role typically requires a bachelor's degree or higher in computer science, data engineering, or a related field, meeting the specialty occupation standard. Candidates with extraordinary ability may qualify for the O-1A. Australians can pursue the E-3 visa, and Canadian and Mexican nationals may qualify under TN visa status in relevant engineering categories.
Which cities in California have the most senior staff data engineer sponsorship jobs?
The San Francisco Bay Area, including San Jose, Mountain View, Menlo Park, and San Francisco itself, accounts for the largest concentration of senior staff data engineer sponsorship activity in California. Los Angeles has a growing presence, driven by media technology and ad-tech companies. San Diego has emerging opportunities linked to biotech and defense technology firms that operate large data infrastructure teams.
How to find senior staff data engineer visa sponsorship jobs in California?
Migrate Mate filters job listings specifically by visa sponsorship availability, making it straightforward to search for senior staff data engineer roles in California without sorting through positions that don't offer sponsorship. The platform is designed for international candidates, so listings are already screened for sponsorship signals. Filtering by state and seniority level on Migrate Mate helps narrow results to the California market efficiently.
Are there state-specific considerations for senior staff data engineers seeking sponsorship in California?
California employers must comply with Department of Labor prevailing wage requirements when filing Labor Condition Applications for H-1B positions, and senior staff-level roles in the Bay Area typically fall into the highest prevailing wage tiers given the local wage benchmarks. California's strong labor protections also mean employers are generally experienced with compliance obligations. University programs at UC Berkeley, Stanford, and UCLA feed a well-established pipeline of advanced engineering talent into sponsoring firms.
What is the prevailing wage for sponsored senior staff data engineer jobs in California?
U.S. employers sponsoring a visa must pay at least the prevailing wage, which is what workers in the same role, area, and experience level typically earn. The Department of Labor sets this rate to make sure companies aren't hiring foreign workers simply because they'd accept lower pay than a U.S. worker. It varies by job title, location, and experience. You can look up current prevailing wage rates for any occupation and location using the OFLC Wage Search page.