Senior Staff Data Engineer Jobs
Senior Staff Data Engineer jobs are open across technology, financial services, healthcare, and media, from staff-level to distinguished engineer, with specializations in data platform architecture, streaming pipelines, and analytics infrastructure. Find a role that fits from the openings below and apply directly.
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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
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Find JobsSenior Staff Data Engineer Job Market
A snapshot from current openings nationwide, updated as new roles post.
Who's Hiring
- Zoox19

- Nuro12

- Intuit11

- Apple8

- GEICO8

Top Industries Hiring
- Technology & Software124
- Artificial Intelligence28
- Electronics & Hardware25
- Automotive24
- Transportation & Logistics13
What Employers Look For
The qualifications that appear most often in senior staff data engineer jobs.
- 8 or more years of experience building and maintaining large-scale data pipelines
- Deep proficiency with distributed processing frameworks such as Apache Spark or Flink
- Experience designing data platform architecture including lakes, warehouses, and mesh patterns
- Fluency in Python or Scala alongside SQL for transformation and orchestration work
- Hands-on experience with cloud data services on AWS, GCP, or Azure
- Demonstrated ability to lead technical design reviews and mentor senior engineers
Tips for Your Senior Staff Data Engineer Job Search
Quantify pipeline scale on your resume
Hiring managers at the senior staff level care about scope. Replace vague claims with concrete throughput numbers, data volumes, and latency improvements your systems achieved. A resume that names terabyte-scale ingestion or sub-second SLA wins beats one that lists tools alone.
Highlight cross-functional design decisions
Senior staff roles are judged on influence, not just execution. Call out moments when you shaped data contracts with upstream engineering teams, drove schema standards org-wide, or resolved competing platform priorities. That cross-team impact is what separates staff from senior engineers in screening.
Target companies by data maturity stage
A senior staff data engineer at a Series B startup owns different problems than one at a Fortune 500. Filter openings by company size and funding stage to find environments where your strengths, whether greenfield builds or scaling legacy systems, are the actual job.
Apply early to roles that fit
Migrate Mate lists senior staff data engineer openings from across the United States in one place, so you can find roles that match and apply directly to each listing.
Prepare a system design narrative not a slide deck
Panels for senior staff data engineers almost always include a whiteboard or live design session. Practice walking through a distributed pipeline decision end-to-end: data sources, transformation logic, storage trade-offs, and failure modes. Interviewers want to see how you reason, not just what you built.
Negotiate scope before negotiating title
At the senior staff level, the real negotiation is often around technical scope, team structure, or platform ownership, not just compensation. Before accepting, clarify what systems you will own, whether the role has a reporting path, and what the first six-month mandate actually is.
Senior Staff Data Engineer Jobs: Frequently Asked Questions
Which companies are hiring the most senior staff data engineers?
The companies hiring the most senior staff data engineers right now include Zoox, Nuro, and Intuit, with the largest share of openings in California, Washington, and New York, based on current listings on Migrate Mate as of June 2026. Demand is concentrated in technology, financial services, and healthcare, though openings appear across a wide range of industries.
How many senior staff data engineer jobs are remote?
About 28% of senior staff data engineer openings are fully remote or hybrid as of June 2026, reflecting the distributed nature of modern data platform work. Roles focused on cloud-native infrastructure, streaming pipeline development, and analytics engineering tend to have the highest remote availability compared to positions requiring close collaboration with on-site data science or ML teams.
How do you become a senior staff data engineer?
Reaching the senior staff level typically requires building production data systems at meaningful scale, taking ownership of platform-wide decisions, and demonstrating impact beyond your immediate team. Most engineers get there by leading migrations or re-architecture projects, establishing data standards adopted by other teams, and consistently mentoring senior engineers. A strong foundation in distributed systems, cloud infrastructure, and data modeling underpins all of it.
Can you land a senior staff data engineer role with limited direct experience at that level?
It is possible if you can demonstrate staff-level impact even without the title. Hiring managers look for evidence that you have owned large technical decisions, influenced engineering direction across teams, and shipped systems others depend on. A portfolio of cross-functional projects, open-source contributions to data tooling, or a clear record of technical leadership in a senior engineer role can substitute for a prior staff-level title.
What does the senior staff data engineer interview process look like?
Most processes run three to five rounds. Expect an initial recruiter or hiring manager screen, followed by a technical coding assessment focused on data manipulation or pipeline logic, a system design session where you architect a distributed data solution end-to-end, and a behavioral round assessing cross-functional leadership and influence. Some companies add a presentation round where you walk through a past project at the architecture level.
Where can I find and apply to senior staff data engineer jobs?
You can find and apply to senior staff data engineer jobs on Migrate Mate, which lists current openings from across the United States. Search the listings to find roles that match your experience and specialization, then apply directly to each one that fits.
See All 238+ Senior Staff Data Engineer Jobs
Jump back to the full list of openings and apply to any senior staff data engineer role that fits.
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