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Afternoon Google Data Analyst Jobs (NOW HIRING)

Power BI Data Analyst Associate Google Data Analytics Professional Certificate Certified Analytics Professional (CAP) AWS Certified Data Analytics - Specialty (for roles involving cloud platforms ...

Power BI Data Analyst Associate • Google Data Analytics Professional Certificate • Certified Analytics Professional (CAP) AWS Certified Data Analytics - Specialty (for roles involving cloud ...

Data Analyst is responsible for collecting, processing, and analyzing data to help make data-driven ... Experience with data visualization tools like Tableau, Power BI, or Google Data Studio. Strong ...

Experience with data visualisation tools like Tableau, Power BI, or Google Data Studio. * Strong analytical and problem-solving skills. * Excellent communication and presentation abilities. * Ability ...

Data Analyst

San Francisco, CA · On-site

$104K - $184K/yr

This role requires a data-driven mindset, strong analytical skills, and experience with ... Experience with Google Analytics, Mixpanel, Amplitude, or similar user analytics tools . * Strong ...

Experience with data visualization platforms like Tableau, Power BI, or Google Data Studio. * Strong understanding of statistical analysis and data modeling. * Excellent problem-solving skills and ...

PR · On-site

$45K - $55K/yr

Experience with Google Analytics , Mixpanel , or similar web/product analytics platforms. * Ability to translate complex data into clear insights and actionable recommendations. * Excellent ...

Experience with tag management systems (Google Tag Manager preferred). * Experience with data ... Experience with server-side analytics platforms. * Exposure to marketing mix modeling or advanced ...

Experience with tag management systems (Google Tag Manager preferred). * Experience with data ... Experience with server-side analytics platforms. * Exposure to marketing mix modeling or advanced ...

Data Analyst

Broomfield, CO · On-site

$70K - $90K/yr

Build, maintain, and optimize dashboards and reports in Google Data Studio (formerly Looker Studio) * Analyze large volumes of payment and transactional data to identify trends, anomalies, and ...

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Afternoon Google Data Analyst information

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$34K

$82.6K

$136K

How much do afternoon google data analyst jobs pay per year?

As of Jul 29, 2026, the average yearly pay for afternoon google data analyst in the United States is $82,640.00, according to ZipRecruiter salary data. Most workers in this role earn between $62,500.00 and $97,000.00 per year, depending on experience, location, and employer.

How much does Google pay a data analyst?

Google data analysts typically earn an average salary ranging from $70,000 to $120,000 annually, depending on experience, location, and level. Entry-level roles may start lower, while experienced analysts with specialized skills or certifications can earn higher salaries. Compensation often includes benefits such as bonuses and stock options.

Is 40 too old to become a data analyst?

Age is not a barrier to becoming a data analyst, as the role values skills in data analysis, programming, and tools like Excel, SQL, and Python. Many professionals transition into data analysis later in their careers, and relevant certifications or training can help demonstrate competence regardless of age.

Is it still worth it to become a data analyst in 2026?

The data analyst role remains valuable in 2026 as organizations continue to rely on data-driven decision-making, with skills in SQL, Excel, and data visualization tools in demand. The profession offers opportunities across industries, and acquiring certifications like Tableau or Power BI can enhance job prospects, though competition and automation trends should be considered. Overall, it remains a viable career choice for those with strong analytical and technical skills.

How many hours is the Google data analytics course?

The Google Data Analytics Professional Certificate typically requires about 120 hours to complete, covering topics such as data cleaning, analysis, and visualization using tools like Excel and Tableau. This self-paced online course is designed for beginners and can be completed over several weeks based on individual schedules.

What is the difference between Afternoon Google Data Analyst vs Morning Google Data Analyst?

AspectAfternoon Google Data AnalystMorning Google Data Analyst
Work HoursTypically works in the afternoon shift, e.g., 1 PM - 9 PMTypically works in the morning shift, e.g., 8 AM - 4 PM
CertificationsRequired: Google Data Analytics Certificate, SQL, Excel skillsRequired: Google Data Analytics Certificate, SQL, Excel skills
Work EnvironmentRemote or office-based, collaborative teamsRemote or office-based, collaborative teams
Industry UsageCommon in tech, finance, marketing sectors

The main difference between an Afternoon Google Data Analyst and a Morning Google Data Analyst lies in their work hours. Both roles require similar skills and certifications, and they often work in similar environments and industries. The choice depends on personal preference for working hours, with both positions offering opportunities in tech and data-driven sectors.

What cities are hiring for Afternoon Google Data Analyst jobs? Cities with the most Afternoon Google Data Analyst job openings:
What are the most commonly searched types of Google Data Analyst jobs? The most popular types of Google Data Analyst jobs are:
What states have the most Afternoon Google Data Analyst jobs? States with the most job openings for Afternoon Google Data Analyst jobs include:

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Re-posted 11 days ago


Job description

TLA is seeking a detail-oriented and analytical Data Analyst to transform complex data sets into actionable business insights. The ideal candidate will be responsible for the full lifecycle of data analysis, including data collection, cleaning, interpretation, and presentation of findings to stakeholders to drive strategic decision-making across the organization.

Key Responsibilities:

  • Data Collection & Management: Collect data from primary and secondary sources, and maintain databases and data systems to ensure accuracy and integrity.
  • Data Cleaning & Preparation: Clean, filter, and transform raw data to remove inconsistencies and prepare it for analysis, ensuring high data quality.
  • Statistical Analysis: Apply appropriate statistical methods and techniques to interpret data, analyze trends, and identify patterns and correlations that provide valuable business insights.
  • Reporting & Visualization: Develop and maintain reports, interactive dashboards, and Key Performance Indicators (KPIs) using data visualization tools to communicate findings in an understandable format for non-technical stakeholders.
  • Problem Solving: Collaborate with cross-functional teams (e.g., Marketing, Finance, Operations) to understand business requirements, define analytical needs, and provide data-driven recommendations to solve complex problems and improve processes.
  • Documentation: Create clear and concise documentation of data sources, analysis processes, and results to ensure reproducibility and transparency.
  • Process Improvement: Identify and implement opportunities to automate and streamline data collection and reporting processes for improved efficiency.

Required Skills and Experience:

         Proficiency in SQL: Essential for querying and managing data in relational databases, including advanced functions like joins and aggregations.

         Strong Excel Skills: Advanced proficiency with spreadsheet software, including pivot tables, VLOOKUP/INDEX-MATCH, and complex formulas for data manipulation and quick analysis.

         Programming Languages: Experience with statistical programming languages such as Python (using libraries like Pandas, NumPy, and Matplotlib) or R for complex analysis and automation.

         Data Visualization Tools: Hands-on experience with Business Intelligence (BI) and data visualization platforms (Tableau or Microsoft Power BI preferred).

         Statistical Knowledge: Solid understanding of statistical concepts, including hypothesis testing, regression analysis, and A/B testing.

Soft Skills

         Analytical and Critical Thinking: The ability to logically approach complex problems, ask the right questions, and evaluate data objectively.

         Communication Skills: Excellent written and verbal communication skills, with the ability to translate technical findings into clear, compelling narratives for diverse audiences.

         Attention to Detail: Meticulous attention to detail to ensure the accuracy and reliability of data and analysis.

         Problem-Solving Abilities: A proactive mindset to troubleshoot data issues and find innovative solutions.

         Collaboration: Strong interpersonal skills and the ability to work effectively within a team environment and with various stakeholders.

Experience and Education

Bachelor's degree in a quantitative field such as Computer Science, Statistics, Mathematics, Economics, or a related discipline.

Preferred Certifications and Qualifications:

While not required, the following certifications are a plus:

         Microsoft Certified: Power BI Data Analyst Associate

         Google Data Analytics Professional Certificate

         Certified Analytics Professional (CAP)

AWS Certified Data Analytics - Specialty (for roles involving cloud platforms)

Requirements

Preferred Certifications and Qualifications:

While not required, the following certifications are a plus:

         Microsoft Certified: Power BI Data Analyst Associate

         Google Data Analytics Professional Certificate

         Certified Analytics Professional (CAP)

AWS Certified Data Analytics - Specialty (for roles involving cloud platforms)