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Data Analyst Python Sql Jobs in Monrovia, CA (NOW HIRING)

Data Analyst - Join Our Team Data Analyst Los Angeles, CA | Full-Time | CTC, W2 Job Summary We are ... Basic knowledge of Python or R (preferred) Skills * Primary skills: Excel, SQL, data visualization ...

Senior Data Analyst

Los Angeles, CA · On-site

$130K - $150K/yr

Build and maintain reusable analytical frameworks, scripts, and tools in Python or SQL to automate recurring analyses, improve data access, and scale the team's capabilities. * Apply statistical and ...

Senior Data Analyst

Los Angeles, CA

$92.70K - $116.90K/yr

Build and maintain reusable analytical frameworks, scripts, and tools in Python or SQL to automate recurring analyses, improve data access, and scale the team's capabilities. * Apply statistical and ...

Senior Data Analyst

Los Angeles, CA

$92.70K - $116.90K/yr

Senior Data Analyst Department: Technology Reports To: Director of Emerging Technologies Location ... Utilize SQL, Python, R, or other tools to extract and manipulate large datasets. Explore ...

Sr Data Analyst

Los Angeles, CA · Hybrid

$89.99K - $143.09K/yr

Key skills include proficiency in SQL, Python, DAX, advanced data analysis, and strong presentation and communications skills. The role also involves fostering collaboration, driving continuous ...

Senior Data Analyst

Pomona, CA · On-site

$86.40K - $109K/yr

Proficiency in data analysis tools such as SQL, Python, R, or similar programming languages. * Experience with data visualization tools (e.g., Tableau, Power BI) to create interactive dashboards.

Senior Data Analyst

Pomona, CA · Hybrid

$86.40K - $109K/yr

Proficiency in data analysis tools such as SQL, Python, R, or similar programming languages. * Experience with data visualization tools (e.g., Tableau, Power BI) to create interactive dashboards.

Senior Data Analyst

Pomona, CA · On-site

$86.40K - $109K/yr

Proficiency in data analysis tools such as SQL, Python, R, or similar programming languages. * Experience with data visualization tools (e.g., Tableau, Power BI) to create interactive dashboards.

... • Strong SQL skills and experience working with large datasets • Experience with data ... Python or R for advanced analytics • Understanding of statistics, experimentation, and ...

... • Strong SQL skills and experience working with large datasets • Experience with data ... Python or R for advanced analytics • Understanding of statistics, experimentation, and ...

Senior Data Analyst

Los Angeles, CA · Hybrid

$92.70K - $116.90K/yr

Senior Data Analyst Location: Century City, CA (Remote / Hybrid role 1-2 days onsite, 3-4 days ... SQL, Python, Tableau, Looker and Excel * Deep understanding of linear / digital platforms and ...

Data Analytics Analyst

Glendale, CA · Hybrid

$69.30K - $103.77K/yr

Use SQL and Python to extract, consolidate, and analyze data from disparate sources - Process Automation: Utilize Google Apps Script and other automation tools to streamline data collection and ...

Data Analytics Analyst

Glendale, CA · Hybrid

$69.30K - $103.77K/yr

Use SQL and Python to extract, consolidate, and analyze data from disparate sources - Process Automation: Utilize Google Apps Script and other automation tools to streamline data collection and ...

Data Analytics Analyst

Glendale, CA · Hybrid

$69.30K - $103.77K/yr

Use SQL and Python to extract, consolidate, and analyze data from disparate sources - Process Automation: Utilize Google Apps Script and other automation tools to streamline data collection and ...

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Data Analyst Python Sql information

See Monrovia, CA salary details

$36.1K

$87.6K

$144.2K

How much do data analyst python sql jobs pay per year?

As of May 29, 2026, the average yearly pay for data analyst python sql in Monrovia, CA is $87,631.00, according to ZipRecruiter salary data. Most workers in this role earn between $66,300.00 and $102,900.00 per year, depending on experience, location, and employer.

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

To thrive as a Data Analyst specializing in Python and SQL, you need strong analytical skills, statistical knowledge, and proficiency in data manipulation, typically supported by a relevant degree or certification. Expertise in Python for data analysis, SQL for database querying, and experience with visualization tools like Tableau or Power BI are commonly expected. Attention to detail, problem-solving abilities, and effective communication are crucial soft skills for interpreting data and presenting actionable insights. These skills help ensure accurate analysis, impactful reporting, and informed decision-making within organizations.

How does a Data Analyst using Python and SQL typically collaborate with other departments within an organization?

Data Analysts proficient in Python and SQL frequently work alongside teams such as marketing, product development, finance, and operations. They gather requirements from stakeholders, translate business questions into data queries, and present actionable insights through dashboards or reports. Regular meetings and clear communication are essential to ensure that data solutions align with business goals, and Data Analysts often act as a bridge between technical data teams and non-technical decision makers. This collaborative environment helps drive data-informed decisions across the organization.

What are Data Analyst Python SQL jobs?

Data Analyst Python SQL jobs involve analyzing and interpreting data to help organizations make informed business decisions. These professionals use Python for data manipulation, automation, and visualization, and SQL for querying and managing data stored in relational databases. Typical tasks include data cleaning, building reports, extracting insights, and creating dashboards. Data Analysts often collaborate with other teams to understand data requirements and communicate findings through presentations or visualizations. Proficiency in both Python and SQL is essential for efficiently handling large data sets and solving complex analytical problems.

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

AspectData Analyst Python SqlData Scientist
Required SkillsExcel, SQL, Python basics, data visualizationAdvanced Python, machine learning, statistical modeling
Work EnvironmentBusiness intelligence, reporting, dashboardsPredictive modeling, research, complex data analysis
Industry UsageFinance, marketing, retail, healthcareTech, finance, research institutions, startups

While Data Analysts with Python and SQL focus on interpreting data, creating reports, and visualizations, Data Scientists build predictive models and perform advanced statistical analysis. Both roles require Python and SQL skills, but Data Scientists typically have a stronger background in statistics and machine learning, making their work more research-oriented.

What job categories do people searching Data Analyst Python Sql jobs in Monrovia, CA look for? The top searched job categories for Data Analyst Python Sql jobs in Monrovia, CA are:
What cities near Monrovia, CA are hiring for Data Analyst Python Sql jobs? Cities near Monrovia, CA with the most Data Analyst Python Sql job openings:
Data Analyst/CDP Developer (SQL/CDP Integration)

Data Analyst/CDP Developer (SQL/CDP Integration)

iSpace, Inc

Torrance, CA • Hybrid

Other

Posted 29 days ago


Job description

Data Analyst/CDP Developer (SQL/CDP Integration)
Location: Torrance, CA (Hybrid of 4 days/week onsite along with 1 day/remote)
Contract Duration – March 2026 – March 31, 2028
As a Data Analyst / CDP Developer, this person will support the customer data platform, improve data quality, implement scalable data solutions, and address end to end data challenges. This role requires advanced SQL development, CDP integration, pipeline operations, and troubleshooting across large scale datasets. The ideal candidate is highly analytical, detail oriented, and thrives in a fast paced, cross functional environment.
Responsibilities will include the following:
Data Analysis and Development

  • Analyze customer data, event, and large-scale datasets to generate insights, validate data quality, and support business decision-making.
  • Write, optimize, and maintain advanced SQL queries across Presto, Hive, and NoSQL systems.
  • Use Python to support data processing, automation, workflow operations, and API integrations.
  • Work within cloud platforms (primarily AWS) and apply general cloud data architecture principles.
  • Perform exploratory data analysis to validate assumptions, identify anomalies, and support stakeholder requirements.
  • Document data processes, business rules, logic, and workflows in Confluence or similar platforms.
  • Collaborate with engineering, analytics, marketing, CRM teams, and SMEs to define data requirements and ensure accuracy.
  • Operate CDP workflow orchestration tools (e.g., Digdag, TD Workflows) to manage pipelines and scheduled jobs.
  • Enhance and monitor data quality frameworks including validation checks, alerts, and pipeline observability.
  • Follow CI/CD and Git-based version control best practices for SQL, scripts, and documentation.
  • Ensure adherence to privacy and compliance standards (GDPR, CCPA, PII).
  • Solve end-to-end data challenges—from ingestion through transformation to analysis and activation.
  • Maintain rigorous attention to detail, especially with customer-level and production data.
  • Proactively improve automation, data quality, workflow reliability, and system performance.
  • Communicate insights and technical concepts clearly to both technical and non-technical audiences.
  • Partner with SMEs to understand business context, refine requirements, and validate solution accuracy.

  Troubleshooting & Support:

  • Diagnose and resolve data pipeline failures, ingestion issues, and workflow errors in a timely manner.
  • Perform root cause analysis using logs, pipeline metadata, and system monitoring tools.
  • Support production environments by monitoring scheduled jobs, validating outputs, and ensuring data accuracy and availability.
  • Implement fixes, patches, and process improvements to prevent recurring problems.
  • Maintain clear documentation of issues, resolutions, and preventive actions to strengthen operational reliability.

Required Skills and Expertise:  

  • Bachelor''s degree in Data Science, Computer Science, Information Systems, Engineering, or a related field.
  • 5+ years of combined experience across data analysis, data engineering, or data operations.
  • Advanced SQL and Query Optimization (Presto, Hive, NoSQL)
  • Expertise in writing complex SQL queries optimizing them for large-scale datasets.
  • Experience with Customer Data Platforms (CDP) and CRM Systems
  • Hands-on experience integrating and managing CDP solutions and CRM platforms to unify and activate customer data.
  • Strong SQL expertise, including complex joins, window functions, CTEs, performance optimization.
  • Proficiency with Python for data processing, automation, and APIs.
  • Experience working with customer data, event data, and large-scale datasets.
  • Familiarity with cloud environments such as AWS, Google Cloud Platform, or Azure (S3, IAM, data storage concepts).
  • Ability to perform exploratory analysis, validate data quality, and present insights to stakeholders.
  • Understanding of data modeling, schema design, identity resolution, and profile unification.
  • Comfortable documenting processes, transformations, and analytical logic in Confluence or similar platforms.
  • Strong communication skills and the ability to work with cross-functional teams
  • Hands-on experience with Treasure Data CDP or similar CDPs (Informatica, Adobe, Salesforce, mParticle, Tealium).
  • Experience with workflow orchestration tools (Digdag, TD Workflows).
  • Experience with data quality frameworks, monitoring, alerting, and pipeline observability.
  • Experience with CI/CD, Git, and version control best practices.
  • Understanding of privacy and compliance (GDPR, CCPA, PII handling).
  • Skilled in providing support to a production environment.
  • Strong problem-solving skills and the ability to deliver end-to-end solutions—from data ingestion to analysis.
  • Excellent attention to detail, especially when working with customer-level and production data.
  • Proactive mindset for improving data quality, automation, and system reliability.
  • Ability to collaborate closely with Subject Matter Experts (SMEs) to understand domain context, validate requirements, and ensure the accuracy and alignment of data solutions.