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Python Data Analyst Jobs in Fontana, CA (NOW HIRING)

V4C.ai

DataBricks Consultant- Onshore

Fontana, CA · On-site

$116K - $139K/yr

Required Qualifications: • 5+ years of experience in Data Engineering, Analytics Engineering, or related technical roles. • Strong SQL skills required. • Strong Python skills required. • ...

Esri

Product Analyst

Redlands, CA · On-site

$70K - $110K/yr

Strong SQL scripting for data extraction, transformation, validation, and analytics-ready dataset creation * Solid knowledge of Python or similar analytical programming languages for modeling and ...

347 Group, Inc.

Be Seen First

Project Control Analyst

Pomona, CA · On-site

$37 - $40.36/hr

Download financial data from various sources (SAP, SharePoint, Excel files) to prepare forecast ... Intermediate experience with python programming, MS Access, MS Office 365 with expert knowledge of ...

Yami

Senior Business Analyst

Brea, CA · On-site

$95K - $123K/yr

Proactively analyze retail, e-commerce platform,and user data to generate insights that drive ... Proficient in MySQL and Tableau; experience with Python isa plus. * Strong logical thinking ...

FocusKPI

Marketing Operations Analyst

Pomona, CA

Comfortable with Python. * Experience working within data platforms like Databricks/Snowflake, and analytics modeling platforms such as Tableau * Strong analytical and problem-solving skills with the ...

Judge Group, Inc.

Analyst-Systems 4

San Dimas, CA · Hybrid

$60 - $70/hr

Strong background in data analysis using tools such as Python, Power Automate, and Power BI. * Expertise in data mining (extracting and gathering data from databases, APIs, repositories)

CWILL

Data Engineer - Bilingual Mandarin required

Norco, CA · On-site

$123K - $147K/yr

This is not a pure data analysis, BI reporting, or one-off scripting role. It is a comprehensive ... Python for API integration, data processing, automation scripting, and file handling • ...

CWILL

Data Engineer - Bilingual Mandarin required

Norco, CA · On-site

$123K - $147K/yr

This is not a pure data analysis, BI reporting, or one-off scripting role. It is a comprehensive ... Python for API integration, data processing, automation scripting, and file handling • ...

Prosum Inc.

Sr. Programmer Analyst

Redlands, CA · On-site

$44.75 - $60.50/hr

Adobe Experience Platform (AEP) Data Collection / Adobe Launch * Google Tag Manager (GTM) * Tealium ... Python scripting experience for automation or analytics workflows * Familiarity with crawling and ...

OC Sports and Entertainment

Data Scientist

Anaheim, CA

$100K - $140K/yr

Own the full analytical lifecycle, from problem definition and data extraction through modeling ... Production-grade Python and advanced SQL experience, with strong attention to performance ...

OC Sports and Entertainment

Data Scientist

Anaheim, CA · On-site

$100K - $140K/yr

Own the full analytical lifecycle, from problem definition and data extraction through modeling ... Production-grade Python and advanced SQL experience, with strong attention to performance ...

OCVIBE

Data Scientist

Anaheim, CA · On-site

$100K - $140K/yr

Own the full analytical lifecycle, from problem definition and data extraction through modeling ... Production-grade Python and advanced SQL experience, with strong attention to performance ...

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All JobsPython Data Analyst JobsPython Data Analyst Jobs in Fontana, CA

Python Data Analyst information

See Fontana, CA salary details

$34.6K

$84K

$138.3K

How much do python data analyst jobs pay per year?

As of Jun 16, 2026, the average yearly pay for python data analyst in Fontana, CA is $84,016.00, according to ZipRecruiter salary data. Most workers in this role earn between $63,500.00 and $98,600.00 per year, depending on experience, location, and employer.

What does a Python Data Analyst do?

A Python Data Analyst leverages the Python programming language to collect, process, and analyze large sets of data. They use tools and libraries like Pandas, NumPy, and Matplotlib to clean data, perform statistical analysis, and create visualizations that help organizations make data-driven decisions. Their role often involves extracting insights from complex datasets, automating data workflows, and communicating findings to stakeholders through reports or dashboards. Python Data Analysts play a crucial part in turning raw data into actionable business intelligence.

How do Python Data Analysts typically collaborate with other departments within an organization?

Python Data Analysts often work closely with teams such as marketing, finance, and product development to provide data-driven insights that inform business decisions. They regularly participate in cross-functional meetings to understand departmental objectives, gather requirements for data analysis, and present their findings in an accessible manner. Effective communication and the ability to translate technical results into actionable recommendations are essential, as analysts often act as a bridge between technical data and non-technical stakeholders.

What is the difference between Python Data Analyst vs Data Scientist?

AspectPython Data AnalystData Scientist
Required SkillsPython, SQL, data visualization, statistical analysisPython, R, machine learning, statistical modeling
Work EnvironmentBusiness analytics, reporting, data cleaningAdvanced modeling, predictive analytics, research
Industry UsageFinance, marketing, healthcare, retailTech, finance, research, AI development

While both roles require Python and data analysis skills, Data Scientists typically engage in more complex modeling and machine learning, whereas Python Data Analysts focus on data cleaning, visualization, and reporting to support business decisions.

What Does a Python Data Analyst Do?

As a Python data analyst, you use the Python programming language to develop tools for data mining, analysis, and data visualization. You typically develop a script to meet the specific data needs of your client or employer. Then, you test your code and perform debugging duties before deploying it in a live environment. Some data analysts also have algorithm creation responsibilities. In this case, after creating and testing an algorithm, you use Python with your algorithm to interpret data. You also develop reports to show to your clients or employers, and you may code a web app or interface that clients can use to visualize data sets.

Are Python coders still in demand?

Python data analysts are currently in high demand due to the language's versatility in data analysis, machine learning, and automation. Skills in libraries like Pandas, NumPy, and experience with data visualization tools increase employability across various industries.

Is 40 too old to become a data analyst?

Age is not a barrier to becoming a data analyst. Many professionals successfully transition into data analysis at various ages by acquiring skills in programming languages like Python or SQL, and gaining experience with data visualization tools. Employers value skills and experience over age, and continuous learning can help you stay competitive in the field.

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

To thrive as a Python Data Analyst, you need strong analytical skills, a solid grasp of statistics, and proficiency in Python programming, often supported by a degree in data science, mathematics, or a related field. Familiarity with data analysis libraries like pandas and NumPy, visualization tools such as Matplotlib or Seaborn, and experience with data querying languages like SQL are typically required. Attention to detail, critical thinking, and effective communication help you derive insights and present findings clearly to stakeholders. These skills and qualities are vital for transforming raw data into actionable business intelligence and supporting data-driven decision-making.

Is Python useful for data analysts?

Python is highly useful for data analysts as it offers powerful libraries like Pandas, NumPy, and Matplotlib for data manipulation, analysis, and visualization. It is widely used in the industry for automating tasks, building data pipelines, and performing statistical analysis, making it a valuable skill for the role.

Will AI replace data analysts?

AI is transforming the role of data analysts by automating routine tasks such as data cleaning and basic analysis, but it is unlikely to fully replace them. Data analysts are needed to interpret complex insights, make strategic decisions, and develop models that require domain expertise and critical thinking. Skills in programming, data visualization, and understanding AI tools remain valuable in this evolving field.
More about Python Data Analyst jobs
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Python Data Analyst jobs near you
Infographic showing various Python Data Analyst job openings in Fontana, CA as of June 2026, with employment types broken down into 3% As Needed, 36% Full Time, 49% Part Time, 1% Temporary, 10% Contract, and 1% Nights. Highlights an 82% Physical, 7% Hybrid, and 11% Remote job distribution, with an average salary of $84,016 per year, or $40.4 per hour.

DataBricks Consultant- Onshore

V4C.ai

Fontana, CA • On-site

$116K - $139K/yr

Full-time

Posted 21 days ago

Job description

Job Title: Data Engineer

Employment Type: Fulltime/Contract

Location: Fontana, CA (Hybrid)

Job Description:

This role will support the organization’s expanding cloud data platform and future enterprise analytics roadmap within Databricks. The Senior Data Engineer will work closely with internal business units and external engineering partners to support enterprise data pipelines, cloud database environments, operational analytics, system integrations, and future data development initiatives.

The position will play a key role in supporting current and future Databricks projects and sprint initiatives, including transportation and brokerage analytics, operational KPI reporting, driver payroll and activity-based pay analytics, telematics and reefer visibility integrations, customer visibility platforms, trailer and yard management integrations, AI and automation initiatives, and enterprise reporting solutions.

This role will support scalable cloud-based data solutions utilizing Databricks, SQL, Python, PySpark, AWS, Microsoft Azure, APIs, and modern ETL/ELT workflows across multiple operational systems and business units.

The ideal candidate will have experience working with large operational datasets, cloud data environments, transportation management systems, telematics platforms, APIs, and modern analytics workflows within a fast-paced logistics and transportation environment.

Key Duties and Responsibilities:

• Develop and maintain scalable data solutions within Databricks.

• Build and optimize ETL/ELT workflows using SQL, Python, and PySpark.

• Support Bronze, Silver, and Gold layer data architecture and scalable analytics workflows.

• Optimize Spark workloads and data transformations for scalability and performance.

• Support ingestion workflows from APIs, operational systems, and external data providers.

• Work with structured and semi-structured datasets including JSON, CSV, and API responses.

• Support AWS-based cloud environments and Databricks integrations.

• Write and optimize advanced SQL queries and transformations.

• Develop Python scripts and Databricks notebooks for automation, validation, and operational analytics.

Required Qualifications:

• 5+ years of experience in Data Engineering, Analytics Engineering, or related technical roles.

• Strong SQL skills required.

• Strong Python skills required.

• Experience with Databricks, PySpark, and Spark-based processing required.

• Experience working in AWS and Microsoft Azure cloud environments and modern ETL/ELT workflows.

Preferred Skills and Experience:

• Logistics / transportation industry experience preferred.

• Experience with Revenova, Samsara, and transportation operational datasets preferred.

• Bachelor’s degree in Computer Science, Data Analytics, Information Systems, Engineering, Mathematics, or related technical field preferred; equivalent experience accepted.

• Understanding of transportation workflows, APIs, JSON data structures, and operational analytics.

• Experience supporting hybrid AWS and Azure cloud architectures, integrations, and enterprise analytics environments preferred.

•Experience with Microsoft Azure services, Microsoft Entra ID (Azure AD), and enterprise identity/access management preferred.