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Data Visualization Expert Jobs in California (NOW HIRING)

Lead Azure Data Engineer

Fountain Valley, CA · On-site

$124K - $149K/yr

They are looking for an Azure expert with strong interpersonal collaboration. * Ideally looking for ... Collaborate with data visualization teams to support accurate, timely insights and visualizations.

Data Engineer

Sacramento, CA · On-site

$6.5K - $10K/mo

The Data Engineer applies comprehensive knowledge of data ingestion, integration, consumption, and data visualization techniques, along with expert and analytical modeling methods, to deliver high ...

Experience working with major data visualization or business intelligence tools: Tableau, PowerBI, etc. * Advanced or expert SQL programming * Comfortable designing data schemas, writing user stories ...

Senior Data Scientist

Mountain View, CA · On-site

$149K - $202K/yr

Overview Join the Intuit Customer Success team as a Senior Data Scientist within our Expert Network ... Hands-on experience with data visualization tools like Tableau or Qlik. Strong communication and ...

Senior Data Scientist

San Diego, CA · On-site

$149K - $202K/yr

Overview Join the Intuit Customer Success team as a Senior Data Scientist within our Expert Network ... Hands-on experience with data visualization tools like Tableau or Qlik. Strong communication and ...

Join the Intuit Customer Success team as a Senior Data Scientist within our Expert Network. In this ... Hands-on experience with data visualization tools like Tableau or Qlik. Strong communication and ...

Senior Data Scientist

San Diego, CA · On-site

$149K - $202K/yr

Join the Intuit Customer Success team as a Senior Data Scientist within our Expert Network. In this ... Hands-on experience with data visualization tools like Tableau or Qlik. Strong communication and ...

Senior Data Scientist

San Diego, CA · On-site

$125 - $150/hr

Join the Intuit Customer Success team as a Senior Data Scientist within our Expert Network. In this ... Hands‑on experience with data visualization tools like Tableau or Qlik. * Strong communication ...

Join the Intuit Customer Success team as a Senior Data Scientist within our Expert Network. In this ... Hands-on experience with data visualization tools like Tableau or Qlik. Strong communication and ...

... Expert data wrangler in Python (e.g., Pandas, Polars) with experience working with relational ... visualization and storytelling abilities, capable of translating complex analyses into clear ...

Showing results 41-60

Data Visualization Expert information

See California salary details

$53.3K

$108K

$159.4K

How much do data visualization expert jobs pay per year?

As of Sep 7, 2026, the average yearly pay for data visualization expert in California is $108,017.00, according to ZipRecruiter salary data. Most workers in this role earn between $88,800.00 and $121,400.00 per year, depending on experience, location, and employer.

What is a data visualization expert?

Data Visualization Experts are professionals who specialize in transforming complex data sets into clear, visually engaging graphics and interactive dashboards. Their main goal is to help organizations and stakeholders understand trends, patterns, and insights from data through visuals such as charts, graphs, and maps. They use tools like Tableau, Power BI, or D3.js, and collaborate closely with data analysts and decision-makers. Their work makes data more accessible and actionable for everyone in an organization.

What are the key skills and qualifications needed to thrive as a data visualization expert?

To thrive as a Data Visualization Expert, you need strong analytical skills, proficiency in data modeling, and an educational background in statistics, computer science, or a related field. Expertise with visualization tools like Tableau, Power BI, and programming languages such as Python or R is typically required, along with familiarity with data querying systems like SQL. Exceptional attention to detail, creativity, and effective communication are important soft skills for translating complex data into compelling, actionable insights. These skills ensure that data visualizations are accurate, informative, and accessible, driving better decision-making across organizations.

What are some common challenges data visualization experts face when translating complex data for non-technical stakeholders?

Data Visualization Experts often encounter the challenge of simplifying complex datasets without losing essential details or accuracy. Balancing clarity and depth is key, as stakeholders may have varying levels of data literacy. Additionally, selecting the right visualization type and ensuring accessibility across devices can be difficult. Effective communication and collaboration with both technical and non-technical team members are critical to delivering insights that inform decision-making.

What is the difference between Data Visualization Expert vs Data Analyst?

AspectData Visualization ExpertData Analyst
Required CredentialsBachelor's or higher in Data Science, Computer Science, or related fields; certifications in visualization tools (e.g., Tableau, Power BI)Bachelor's or higher in Statistics, Mathematics, or related fields; often certifications in data analysis tools
Work EnvironmentFocus on creating visual representations, dashboards, and interactive reportsAnalyze datasets, generate insights, and prepare reports, often using visualization tools
Employer & Industry UsageUsed across tech, finance, marketing, and consulting firms for data storytellingCommon in finance, healthcare, marketing, and business intelligence roles

The main difference is that a Data Visualization Expert specializes in designing and developing visual data representations, while a Data Analyst focuses on analyzing data to generate insights, often utilizing visualization tools as part of their workflow.

What are popular job titles related to Data Visualization Expert jobs in California?

For Data Visualization Expert jobs in California, the most frequently searched job titles are:

What job categories do people searching Data Visualization Expert jobs in California look for?

The top searched job categories for Data Visualization Expert jobs in California are:

Infographic showing various Data Visualization Expert job openings in California as of August 2026, with employment types broken down into 1% As Needed, 88% Full Time, 9% Part Time, and 2% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $108,017 per year, or $51.9 per hour.

Lead Azure Data Engineer

3B Staffing LLC

Fountain Valley, CA • On-site

$124K - $149K/yr

Full-time

This job post has expired 2 days ago. Applications are no longer accepted.


Job description

Manager notes:

Antech is building a new Data Engineering team, reporting under the (new) Director of Data Engineering and Governance. (There was no prior centralized role for data engineering and governance).

  • They are working on building an Azure based data platform and migrating to cloud, using Azure Data Lake storage, Databricks and Azure Synapse Analytics.
  • Reporting to Director
  • Currently in planning phase to be in development by February.
  • The Lead position will be involved in the build and support, building the initial cloud data.
  • They are looking for an Azure expert with strong interpersonal collaboration.
  • Ideally looking for someone who can work out of the Fountain Valley office.

Key Responsibilities:

  • Design, build, and maintain Azure-centric data pipelines to ensure efficient data flow across our multi-cloud and on-premises systems.
  • Perform data transformations and manage data tables to support business intelligence, reporting, and data-driven decision-making.
  • Design event-driven solutions to sequence and automate Azure-centric data pipelines.
  • Write and optimize complex SQL queries, develop data models, and manage data tables to enable seamless analytics.
  • Mentor and assist junior ETL and data model developers to ensure operation consistency project deliverables.
  • Prepare summary reports on project progress and operational status to program director.
  • Collaborate with data visualization teams to support accurate, timely insights and visualizations.
  • Collaborate in developing and optimizing a data warehouse, primarily on Azure.
  • Support AI/ML initiatives to enhance and support data processes, predictive modeling, and drive business value for business units.

Key Qualifications:

  • Technical Mastery: Strong proficiency in Azure Cloud Platform, particularly Databricks, Synapse Analytics, Data Factory and Data Lake Storage, Azure SQL, and multi-dimensional data warehouse methodology.
  • ETL Proficiency: Experienced in building ETL (Extract, Transform, Load) workflows that support efficient data movement and processing in cloud environments. Familiarity with sourcing data from leading Saas providers and their API solutions such as Oracle Fusion Cloud ERP, Salesforce CRM and CSM, Workday HCM and relational databases like Oracle, MS SQL Server and Postgres.
  • Data Transformation Skills: Deep understanding of data transformation techniques to ensure accuracy and performance across all systems.
  • Cloud Infrastructure Knowledge: Proficiency with Azure cloud infrastructure management and best practices for data security, scalability, and cost efficiency.
  • Analytical Problem-Solving: Ability to troubleshoot data issues and proactively improve processes to enhance data reliability.
  • Code Optimization: Advanced skills in writing and optimizing complex Python, Java, JSON, Spark and SQL queries for better performance and throughput.
  • Data Modeling Expertise: Proven experience developing efficient data models that support large-scale analytics.
  • Reporting, Analytics and Visualization: Proficiency in Analytics and visualization tools like Power BI, Tableau and Oracle Analytics Cloud.
  • Data Governance: Strong knowledge of data governance practices, including data quality, lineage, data at rest and in-transit security and role-based access control protocols.
  • Collaborative Communication: Ability to work cross-functionally with data scientists, analysts, visualization teams and business users to deliver comprehensive insights.
  • LIMS Familiarity: Familiarity with Laboratory Information Management Systems (LIMS) such as Sunquest Antrim and Sysmex MOLIS is a big plus.
  • AI/ML Experience: Familiarity with applying machine learning models to data processes and enhancing data pipeline functionality.

Daily Responsibilities:
In this role, you'll be managing end-to-end data engineering and automation, ensuring the highest standards of data quality, efficiency, scalability and security. Your day-to-day will include:

  • Pipeline Management: Oversee and refine data pipelines, ensuring data is collected, transformed, and stored accurately across all systems. This includes monitoring and troubleshooting pipelines to prevent data loss, downtime and improve efficiency.
  • ETL Development: Build, maintain, and improve ETL workflows that support data integration from multiple sources, handling various data types and frequencies. This includes event-driven solutions to sequence and automate Azure-centric data pipelines.
  • Data Modeling & Transformation: Collaborate with a Data Management team to design data models that align with business needs and perform data transformations to create usable data sets for analysis and reporting.
  • SQL Query Optimization: Write, test, and optimize SQL queries to ensure efficient data retrieval and processing.
  • Collaboration with Analytics Teams: Work closely with data scientists, analysts, and stakeholders to support data requests, visualization needs, and other analytics functions.
  • Cloud Infrastructure Management: Monitor and manage an Azure Data Platform and collaborate on other cloud platforms (Oracle Cloud, AWS) to maintain scalability and ensure secure data access.
  • Data Quality Assurance: Conduct regular quality checks, clean data sets, and implement data governance practices to maintain accuracy and reliability.
  • Documentation & Reporting: Keep thorough documentation of data processes, configurations, and workflows. Provide regular updates on system performance and data availability to downstream users and program director.
  • Innovation & Continuous Improvement: Stay up to date on industry trends, experiment with new data tools and techniques, and apply best practices to drive continuous improvement.

AI/ML Integration: Support