Data Platform Engineer Jobs in California
Data Platform Engineer jobs in California are among the most active in the country, concentrated in technology, cloud infrastructure, financial services, and entertainment, with demand at every level from junior data engineers through principal and staff engineers. The largest hiring metros are San Francisco, Los Angeles, and San Jose, where companies like Google, Salesforce, and Netflix maintain substantial engineering organizations with ongoing data platform needs. The most in-demand specialties include cloud-native pipeline development, distributed systems architecture, and real-time data streaming. Find a role that fits below and apply directly.
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INTRODUCTION
Ellipsis Health is creating cutting-edge AI/ML products that solve healthcare staffing challenges and administrative burdens using conversational AI and our patented voice biomarker technology - helping deliver better healthcare for everyone. We are currently looking for an experienced Senior Data Platform Engineer, with significant experience in building, scaling, and optimizing modern data platforms across public cloud environments. We are located in the San Francisco Bay Area, but we are open to remote candidates for this role anywhere in the US.
Responsibilities
- Lead the design, development, and operation of a scalable and secure data platform to support analytics, ML Ops, and business intelligence
- Collaborate closely with Data Science, Machine Learning, Application and DevOps teams to implement end-to-end ML Ops pipelines
- Architect and manage data warehousing solutions using Databricks, Dbt, and Spark
- Develop and maintain ETL/data pipelines that handle structured and unstructured data across diverse sources
- Optimize data storage, access, and processing for cost-efficiency and performance in GCP and AWS Cloud environments
- Build and maintain dashboards and analytics solutions using tools such as Sigma, Metabase, and other BI platforms
- Ensure compliance with data governance, security, and privacy best practices, including HIPAA, SOC-2, and other regulatory requirements
- Evaluate and integrate third-party anonymization and security solutions to protect sensitive data
- Provide strategic guidance on the evolution of the data platform to meet the company's growth and technical needs
- Design and implement scalable infrastructure for Large Language Model (LLM) operations, including training, fine-tuning, and inference workflows
- Collaborate with AI/ML teams to build and optimize LLM serving platforms for real-time and batch processing
- Develop monitoring and observability solutions for LLMs, ensuring model performance, cost-efficiency, and compliance with ethical AI guidelines
- Evaluate and integrate state-of-the-art LLM technologies into existing data platforms to enhance analytics and decision-making
BASIC QUALIFICATIONS
- Bachelor's or Master's Degree in Computer Science or equivalent experience
- 5+ years of industry experience in designing and building large-scale data platforms
- Strong expertise in SQL, Data Modeling, and Data Warehousing (Databricks, Snowflake, Redshift, BigQuery, etc.)
- Proficiency in writing Advanced SQLs and performance tuning
- Strong proficiency in Python for building, optimizing, automating and maintaining data pipelines and services
- Deep experience with Apache Spark and distributed data processing frameworks
- Hands-on experience with modern ETL/Orchestration frameworks such as Airflow, dbt, and others
- Knowledge of business intelligence tools such as Sigma, Metabase, Tableau, and Looker
- Strong familiarity with cloud-based infrastructure and managed data services in GCP and AWS Cloud
- Experience with CI/CD pipelines to automate testing, deployment and release of data engineering and analytics workflows using GitLab, GitHub etc
- Experience with tools like Kubernetes, Terraform, Pubsub, Debezium
- Exposure building data quality frameworks and automation
- Understanding of data governance, privacy, and regulatory frameworks (HIPAA, SOC-2, HITRUST)
PREFERRED QUALIFICATIONS
- Experience working with ML Ops platforms and supporting Data Science teams
- Experience with ML Ops tools such as MLflow, Streamlit, and vector databases
- Familiarity with healthcare data standards (FHIR, HL7)
- Experience in real-time data processing and event-driven architectures
- Expertise in implementing data access controls and anonymization techniques
SALARY AND BENEFITS
We offer competitive salary and benefits, including 401(k) matching, health, vision, and dental insurance, and very flexible paid time off. The typical salary range for this role is $150,000 to $170,000 USD, depending on skills, qualifications, and relevant experience.
BACKGROUND CHECKS
As a health technology company, we reserve the right to run background checks on candidates to whom we extend offers, in compliance with applicable laws. We evaluate candidates holistically and comply with all “ban the box” regulations.
ASSISTANCE
If you have a disability or require accommodations during the application or recruitment process, please contact careers@ellipsishealth.com.
See All 105+ Data Platform Engineer Jobs in California
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Find Data Platform Engineer JobsData Platform Engineer Jobs by City in California
Where California roles are concentrated, by current openings.
Data Platform Engineer Job Market in California
A snapshot from current California openings, updated as new roles post.
Who's Hiring
- Nuro9

- NVIDIA7

- Guidewire Software4

- Pinterest4

- Discord3

Top Industries Hiring
- Technology & Software65
- Science & Research7
- Artificial Intelligence6
- Electronics & Hardware6
- Biotechnology & Pharmaceuticals4
What California Employers Look For
The qualifications that appear most often in data platform engineer jobs across California.
- Bachelor's or master's degree in computer science, data engineering, or a related technical field
- Hands-on experience with distributed data frameworks such as Apache Spark, Flink, or Kafka
- Proficiency with cloud platforms including Google Cloud, AWS, or Azure and their managed data services
- Experience designing and maintaining scalable data pipelines using tools like dbt, Airflow, or Databricks
- Strong SQL skills combined with at least one programming language such as Python, Scala, or Java
- Familiarity with data governance, data quality frameworks, and metadata management practices
Data Platform Engineer Jobs in California: Frequently Asked Questions
How do you become a data platform engineer in California?
Data platform engineering has no state-issued license or California-specific credential, so the path runs through education and demonstrated technical skills. Most California employers look for a bachelor's degree in computer science, software engineering, or a related field, though a strong portfolio of pipeline and infrastructure projects can substitute at some companies. Building experience with cloud platforms dominant in California's tech industry, particularly Google Cloud and AWS, and contributing to open-source data projects strengthens a candidacy considerably.
How much do data platform engineers make in California?
Data platform engineers in California earn a median of about $170,160 a year, based on May 2025 Bureau of Labor Statistics wage data, ranging from around $101,200 for the lowest 10% to over $227,900 for the top 10%. Pay rises with experience, specialty, and employer.
Which companies hire data platform engineers in California?
Employers hiring data platform engineers in California right now include Nuro, NVIDIA, and Guidewire Software, based on current listings on Migrate Mate as of June 2026. California's concentration of technology headquarters, streaming media companies, and fintech firms means demand stays consistent across both large enterprise organizations and well-funded mid-stage companies in the Bay Area and Los Angeles.
Which California cities have the most data platform engineer jobs?
San Francisco, Mountain View, and Santa Clara account for the most data platform engineer openings in California. San Francisco and San Jose lead because of the Bay Area's density of technology headquarters and cloud infrastructure companies, while Los Angeles reflects growing demand from entertainment tech, adtech, and a rapidly expanding startup ecosystem that increasingly relies on sophisticated data platforms.
Are there remote data platform engineer jobs in California?
Yes, and more than most fields. About 29% of data platform engineer openings tied to California are remote or hybrid as of June 2026, reflecting the fundamentally desk-based and collaborative-tooling nature of the work. Pipeline development, data modeling, and infrastructure-as-code tasks are particularly well suited to remote arrangements, though roles involving close cross-functional collaboration with on-site analytics or product teams more often carry a hybrid expectation.
How can I get hired as a data platform engineer in California with little or no experience?
The most realistic entry path is through an adjacent technical role such as data analyst, analytics engineer, or software engineer, then moving into platform work as you build pipeline and infrastructure skills. Large California technology employers like Google, Apple, and Salesforce run university hiring programs and associate software engineer tracks that accept candidates without prior industry experience. Building a public portfolio on GitHub that demonstrates Airflow DAGs, dbt models, or a cloud pipeline project gives hiring managers concrete evidence of ability and meaningfully separates entry-level candidates.
Where can I find and apply to data platform engineer jobs in California?
You can find and apply to data platform engineer jobs in California on Migrate Mate, which lists current California openings updated regularly. Find the roles that fit your experience and target location, then apply directly to the employers posting them.
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