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Data Validator Jobs in California (NOW HIRING)

Data Engineer

Los Angeles, CA · On-site

$123K - $148K/yr

Implement data validation, testing, and monitoring within pipelines to catch anomalies and ensure data integrity. * Support dataset versioning and lineage tracking to satisfy IEC 62304 and FDA Design ...

Data Engineer V

Oakland, CA · On-site

$172K/yr

In this role, you will be responsible for building robust data validation frameworks and ensuring that large-scale datasets meet strict compliance standards for reproducibility and lineage. You will ...

Participate in solution validation sessions by helping set up demos, prototypes, or test scenarios ... Data manipulation or reporting experience Growth Path This role is designed as a development ...

The position also oversees production validation testing post-handover, resolves ongoing operational data discrepancies, and maintains high-integrity datasets for performance monitoring, financial ...

Manager, Asset Data Integrity

Irvine, CA · On-site

$100K - $130K/yr

The position also oversees production validation testing post-handover, resolves ongoing operational data discrepancies, and maintains high-integrity datasets for performance monitoring, financial ...

The position also oversees production validation testing post-handover, resolves ongoing operational data discrepancies, and maintains high-integrity datasets for performance monitoring, financial ...

The position also oversees production validation testing post-handover, resolves ongoing operational data discrepancies, and maintains high-integrity datasets for performance monitoring, financial ...

The position also oversees production validation testing post-handover, resolves ongoing operational data discrepancies, and maintains high-integrity datasets for performance monitoring, financial ...

The position also oversees production validation testing post-handover, resolves ongoing operational data discrepancies, and maintains high-integrity datasets for performance monitoring, financial ...

Data Engineer (On-Site)

Orange, CA · On-site

$120K - $140K/yr

Validate data integrity across various source systems (EMR, billing, claims, CRM, etc.). Requirements Gathering & Stakeholder Engagement * Work directly with business units (clinical, operations ...

Data Engineer (On-Site)

Orange, CA · On-site

$120K - $140K/yr

Validate data integrity across various source systems (EMR, billing, claims, CRM, etc.). Requirements Gathering & Stakeholder Engagement * Work directly with business units (clinical, operations ...

Showing results 41-60

Data Validator information

See California salary details

$45.4K

$162.9K

$240.3K

How much do data validator jobs pay per year?

As of Aug 6, 2026, the average yearly pay for data validator in California is $162,857.00, according to ZipRecruiter salary data. Most workers in this role earn between $131,800.00 and $167,800.00 per year, depending on experience, location, and employer.

What skills and qualifications are needed to be a data validator?

To thrive as a Data Validator, you need strong attention to detail, analytical skills, and experience working with large datasets, often supported by a degree in information technology, mathematics, or a related field. Familiarity with data validation tools, database systems (like SQL), Excel, and sometimes industry-standard certifications such as CDMP (Certified Data Management Professional) can be advantageous. Excellent communication, problem-solving abilities, and the capacity to work independently or as part of a team are valuable soft skills. These competencies ensure accuracy, integrity, and reliability in data, which are critical for decision-making and business operations.

What challenges might I face as a data validator, and how can I overcome them?

As a Data Validator, you may encounter challenges like identifying subtle inconsistencies in large datasets, managing tight deadlines for data verification, and adapting to multiple data sources or formats. To overcome these hurdles, it’s important to develop strong troubleshooting skills, stay organized, and leverage automated validation tools whenever possible. Collaborating closely with data engineers and business analysts can also help clarify data requirements and resolve ambiguities. Building a thorough understanding of data processes within your organization will further equip you to handle these challenges effectively and efficiently.

What is a data validator?

A Data Validator is responsible for ensuring the accuracy, consistency, and integrity of data within a system or dataset. They review, clean, and verify data to identify errors, inconsistencies, or missing information. This role is essential in industries that rely on high-quality data for decision-making, such as finance, healthcare, and research. Data Validators use various tools and techniques to cross-check and validate data against predefined standards or business rules. Their work helps maintain data reliability, improves efficiency, and supports better decision-making across an organization.

What are the most commonly searched types of Data Validator jobs in California? The most popular types of Data Validator jobs in California are:
Infographic showing various Data Validator job openings in California as of August 2026, with employment types broken down into 70% Full Time, and 30% Contract. Highlights an 100% In-person job distribution, with an average salary of $162,857 per year, or $78.3 per hour.

$123K - $148K/yr

Other

PTO

Re-posted 19 days ago


Job description

Open Position - Data Engineer

Horizon Surgical Systems Inc.

Horizon Surgical Systems Inc. is revolutionizing the world of surgical ophthalmology by developing a novel, AI driven, and imaging-guided surgical robotic system. Horizon Surgical Systems Inc. aims to expand access to care, provide superior capabilities to the human surgeon, and enhance patient outcomes. Microsurgery in general and Ophthalmology are subfields of surgery for which the surgical outcomes can be significantly improved by robotic systems to allow superior dexterity, precision, accuracy, and visualization beyond the human surgeon's own capabilities.

We are seeking highly motivated, and intellectually inquisitive individuals looking to make a positive impact on healthcare via the development of robotic technology. The core values of Horizon Surgical Systems Inc. are:

  • Commitment to Excellence: We aim to deliver superior patient outcomes and surgeon experiences
  • Passion for Creativity and Innovation: We are driven by new ideas and aim to push the boundaries of what's possible
  • Teamwork and Camaraderie: We achieve our best when we collaborate and work together
  • Welcoming of Critical Opinion: We are enriched by constructive criticism and support the best ideas
  • Personal Accountability: We honor our commitments and take responsibility for our actions

Horizon Surgical Systems Inc. offers:

  • An opportunity to build autonomous surgical robotic systems driven by image guidance and AI technology for the future of affordable, high-quality healthcare.
  • The opportunity to work alongside clinicians, engineers, and global leaders in cutting-edge AI, imaging, and robotics technology.
  • Competitive compensation and an excellent company-paid benefits package.
Role:

The Data Engineer is responsible for designing, building, and maintaining the data pipelines that power AI model training, validation, and regulatory workflows for autonomous surgical robotics systems. Working alongside the Data Operations Analyst, this role focuses on the engineering side of the data lifecycle: architecting reliable, scalable pipelines in Dagster, modeling data in SQL, and writing production-quality Python. The ideal candidate brings strong fundamentals in SQL and Python; and is eager to deepen their data engineering expertise in a fast-paced, regulated environment.

Essential Duties and Responsibilities
  • Design, build, and maintain data pipelines in Dagster to support AI model training, validation, and regulatory submission workflows.
  • Write and optimize SQL for data transformation, modeling, and quality validation across the data platform.
  • Develop Python-based tooling and automation to support data ingestion, transformation, and delivery.
  • Collaborate with the Data Operations team to ensure pipeline outputs meet data quality, traceability, and compliance requirements.
  • Build and maintain infrastructure for data ingestion from surgical robotic systems, annotation platforms, and internal sources into cloud storage (AWS S3).
  • Implement data validation, testing, and monitoring within pipelines to catch anomalies and ensure data integrity.
  • Support dataset versioning and lineage tracking to satisfy IEC 62304 and FDA Design History File requirements.
  • Contribute to the design of data models, schemas, and catalogs in coordination with the Data Operations team.
  • Troubleshoot and resolve pipeline failures, performance bottlenecks, and data inconsistencies.
  • Participate in code reviews and contribute to engineering best practices for the data platform.
Required Qualifications
  • Bachelor's degree in Computer Science, Data Science, Software Engineering, or a related field, or equivalent practical experience.
  • 2+ years of experience in data engineering, software engineering, or a related technical role.
  • Strong proficiency in SQL for data transformation and analysis.
  • Strong proficiency in Python for building data pipelines and automation.
  • Experience with cloud infrastructure (AWS preferred) and containerized workflows.
  • Familiarity with version control (Git) and collaborative development workflows.
  • Eagerness to learn and grow in data engineering, including orchestration frameworks, data modeling, and infrastructure-as-code.
  • Effective communication skills for working closely with analysts, ML engineers, and cross-functional teams.
Preferred Qualifications
  • Experience with Dagster or similar orchestration frameworks (Airflow, Prefect).
  • Experience with data warehouse or lakehouse patterns (e.g., Snowflake, Delta Lake, dbt).
  • Exposure to regulated environments (FDA, ISO 13485, IEC 62304) or medical device industry.
  • Familiarity with machine learning data lifecycle concepts (dataset versioning, data drift monitoring, model validation datasets).
  • Knowledge of DICOM, medical imaging data standards, or ophthalmic imaging modalities (OCT, microscopy) is a plus.

This is an exciting opportunity to join a high-tech startup that is poised to revolutionize surgical robotics in ophthalmology. 

The base salary range for this role is $120,000 - $134,000, in addition to a performance-based annual bonus, equity (stock options), a comprehensive benefits package, and a generous PTO policy.