Data Quality Analyst - Chino Hills

Job Title

Data Quality Analyst

$58,000 – $62,000 annually

Full time / Hourly

Chino Hills, CA

At Redwood Family Care Network, data is more than numbers—it is how we protect people, improve lives, and deliver world‑class, person‑centered services. The Data Quality Analyst plays a critical role in advancing Redwood’s Mission, Vision, and Core Values by ensuring the accuracy, integrity, and reliability of the data that informs quality assurance, compliance, and operational decision‑making across our Intellectual and Developmental Disabilities (IDD) services.

This role supports Redwood’s commitment to People, Integrity, Continuous Improvement, Innovation, and Empowerment by maintaining trusted reporting systems, translating data into meaningful insights, and strengthening accountability across teams. The Data Quality Analyst works within existing platforms and dashboards, focusing on validation, consistency, and trend interpretation—not advanced modeling—so leadership can confidently act on the information presented. This position offers growth and development within a mission‑driven organization that values learning, collaboration, and using data as a tool to improve outcomes for the individuals we support, the employees we invest in, and the communities we serve.

Redwood Family Care Network takes a ZERO tolerance stance on abuse and neglect. Any allegations will be reported to the proper authorities. We are committed to the Health and Safety of the individuals we support.

• Foundational knowledge of data analysis concepts, including data accuracy, validation, and integrity principles.
• Understanding of business intelligence and reporting practices, including dashboard interpretation and recurring report cycles.
• Basic knowledge of trend analysis and simple forecasting techniques used to evaluate historical data patterns.
• Familiarity with working in structured data environments using existing systems and standardized data definitions.
• General knowledge or ability to quickly adapt to reporting on quality assurance and compliance within regulated environments (healthcare, human services, or similar).
• Awareness of data confidentiality, privacy, and appropriate data handling practices.

• Skill in reviewing, validating, and reconciling data to ensure accuracy and completeness.
• Proficiency in Excel or Google Sheets, including formulas, filters, pivot tables, and data organization techniques.
• Ability to use business intelligence or reporting tools (e.g., Power BI, Tableau, Looker, or similar) to maintain and interpret dashboards.
• Skill in identifying trends, patterns, and variances within datasets and summarizing findings clearly.
• Ability to prepare consistent, repeatable reports on weekly and monthly timelines.
• Written and verbal communication skills sufficient to explain data findings to non‑technical audiences.
• Organizational skills to manage multiple reporting deadlines and tasks with attention to detail.

• Ability to work accurately within existing data platforms and systems without introducing errors or inconsistencies.
• Ability to follow established procedures and data governance standards.
• Ability to interpret data and translate findings into clear, actionable insights with guidance from leadership.
• Ability to recognize data anomalies and elevate issues appropriately.
• Ability to maintain confidentiality and exercise sound judgment when handling sensitive information.
• Ability to work independently on routine tasks while collaborating effectively with Quality, Compliance, and Operations teams.
• Ability to adapt to evolving reporting requirements and priorities in a regulated environment.

• Bachelor’s degree in Data Analytics, Statistics, Information Systems, Business Analytics, Public Health, or a related field (or AA with equivalent experience).
• 1–3 years of experience in data analysis, reporting, quality, or administrative analytics.
• Experience working with structured datasets and recurring report systems.

• Working Knowledge Of Data Analysis Methods, Including:
• Trend and variance analysis
• Data validation and quality checks
• Basic forecasting or predictive…