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Data Profiling Jobs in California (NOW HIRING)

Expertise in data quality frameworks, data profiling, and data validation techniques. * Hands-on experience with data standardization, including address standardization and enrichment. * Familiarity ...

Carlsbad, CA Duration: 6 Months • Strong data analysis and data profiling skills • Strong Conceptual, Logical and Physical data modeling for VLDB Data warehouse • Hands on experience with ...

... Profiling and Data Analysis 3) Good amount of experience with SQL / Oracle 4) Health care claims data knowledge (Good To have) 5) Health care or Life science domain knowledge is Must Additional ...

Master Data Manager

Anaheim, CA · On-site

$150K - $190K/yr

Implement data profiling, monitoring, and remediation processes * Lead root cause analysis for recurring data issues * Own selection, implementation, and optimization of MDM platforms/tools * Define ...

Sr Data Analyst

Newport Beach, CA

$92K - $116K/yr

Strong hands-on experience in data analysis using SQL, Python, and data profiling techniques to identify anomalies, data quality issues, gaps, and inconsistencies across source and target systems.

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Data Profiling information

See California salary details

$33.6K

$81.6K

$134.2K

How much do data profiling jobs pay per year?

As of Jul 23, 2026, the average yearly pay for data profiling in California is $81,558.00, according to ZipRecruiter salary data. Most workers in this role earn between $61,700.00 and $95,700.00 per year, depending on experience, location, and employer.

Is 40 too late for data science?

Data profiling is a key skill in data science, and individuals can enter the field at any age with relevant skills such as SQL, Python, and data analysis. Many professionals successfully transition into data science later in their careers by gaining certifications and practical experience, making age less of a barrier than skill development and continuous learning.

Does the FBI hire data analysts?

Yes, the FBI employs data analysts to support investigations, intelligence analysis, and operational decision-making. These roles often require strong analytical skills, knowledge of data management tools, and security clearances, with positions available through federal hiring processes.

What is the difference between Data Profiling vs Data Analyst?

AspectData ProfilingData Analyst
Primary FocusAnalyzing data for quality, structure, and patternsInterpreting data to generate insights and reports
Skills RequiredData analysis, SQL, data quality toolsData analysis, visualization, statistical skills
Work EnvironmentData warehouses, ETL processes, data governanceBusiness intelligence tools, dashboards, reporting platforms
CertificationsData quality certifications, SQL certificationsData analysis certifications, Tableau, Excel

Data Profiling primarily involves examining data sets to assess quality and structure, often as a preliminary step in data management. Data Analysts focus on interpreting data to provide actionable insights and support decision-making. While both roles require analytical skills and familiarity with data tools, Data Profiling emphasizes data quality and structure, whereas Data Analysts concentrate on analysis and reporting.

What does a data profiler do?

A data profiler analyzes datasets to assess their quality, structure, and content, identifying issues such as missing values, inconsistencies, or anomalies. This process helps ensure data accuracy and readiness for analysis or integration, often using tools like SQL, Python, or specialized data profiling software.

What are the key skills and qualifications needed to thrive as a Data Profiling Specialist, and why are they important?

To thrive as a Data Profiling Specialist, you need a solid understanding of data analysis, data quality assessment, and database management, often supported by a degree in computer science or a related field. Familiarity with profiling tools such as Informatica, Talend, or Microsoft SSIS, as well as proficiency in SQL and data visualization software, is typically required. Strong attention to detail, analytical thinking, and effective communication skills help you interpret results and convey findings to stakeholders. These skills and qualities are crucial for ensuring data accuracy, driving informed business decisions, and improving overall data governance.

What is data profiling?

Data profiling is the process of examining, analyzing, and summarizing data from existing sources to understand its structure, content, and quality. It helps organizations identify inconsistencies, errors, and patterns within their data, which is crucial for data quality initiatives, data migration projects, and business intelligence tasks. Data profiling typically involves assessing data types, frequency, uniqueness, and relationships among data elements. The insights gained enable better data management, improved decision-making, and more efficient data integration.

What are some typical challenges faced in a data profiling role and how can they be addressed?

Professionals in data profiling often encounter challenges such as dealing with incomplete, inconsistent, or poor-quality data from various sources. Addressing these issues requires strong analytical skills, attention to detail, and the use of specialized data profiling tools to identify anomalies and patterns. Collaborating closely with data engineers, business analysts, and stakeholders is essential to communicate findings and recommend improvements, ensuring data quality for downstream processes. Regularly updating profiling techniques and staying current with industry best practices also helps in overcoming evolving data challenges.

Is data analysis a well-paid job?

Data profiling is a specialized data analysis role that often offers competitive salaries, especially for professionals with skills in SQL, data management, and tools like Python or R. Compensation varies by industry, experience, and location, but data analysis roles generally provide good pay compared to many other entry-level positions.
What job categories do people searching Data Profiling jobs in California look for? The top searched job categories for Data Profiling jobs in California are:
Infographic showing various Data Profiling job openings in California as of July 2026, with employment types broken down into 1% As Needed, 83% Full Time, 12% Part Time, 1% Temporary, and 3% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $81,558 per year, or $39.2 per hour.
Data Testing Manager

Data Testing Manager

Staffingine LLC

Irvine, CA • On-site

Contractor

Posted 20 days ago


Job description

Job Title: Sr Data Testing Manager 
Job Location: Irvine, CA 
Job Type: Contract 

Job Description:  

  • Lead and manage end-to-end testing activities for MDM modernization projects. 

  • Develop comprehensive test strategies, plans, and scripts for data migration, integration, and transformation. 

  • Must have experience managing large scale Data modernization initiative and Stakeholders communication. 

  • Validate data quality, consistency, and integrity across multiple systems and platforms. 

  • Collaborate with development, data engineering, and business teams to ensure alignment on requirements and deliverables. 

  • Perform functional, integration, and performance testing for ETL workflows and MDM components. 

  • Ensure compliance with data governance standards and best practices. 

  • Drive address standardization and enrichment testing for customer and vendor data. 

  • Provide defect management and root cause analysis for data-related issues. 

Required Skills & Experience: 

  • 10+ years of experience in software testing with a focus on data-centric projects. 

  • Proven experience in Master Data Management (MDM) initiatives (modernization or implementation). 

  • Strong knowledge of ETL tools and processes (Informatica, Talend, or similar). 

  • Expertise in data quality frameworks, data profiling, and data validation techniques. 

  • Hands-on experience with data standardization, including address standardization and enrichment. 

  • Familiarity with Informatica SaaS MDM (preferred but not mandatory). 

  • Solid understanding of data governance principles and metadata management. 

  • Excellent communication and leadership skills to manage cross-functional teams. 

Nice-to-Have: 

  • Experience with cloud-based data platforms (AWS). 

  • Knowledge of data security and compliance standards. 

  • Exposure to Agile methodologies and tools like Jira, Q - Test and Confluence 

  • Skills 

  • Mandatory Skills: Informatica MDM, MDM Modernization, Data Migration, Integration, Data Profiling, Data Validation, Data Quality, ETL, SaaS MDM, Data Standardization, Data Governance, Metadata Management, AWS, Data Security, Agile, Jira, Confluence.