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Data Analytics Google Jobs (NOW HIRING)

There will be a heavy emphasis on Google Analytics, Google Search Console, Power BI, and other behavioral metric systems. Note: This is a full-stack data position, which requires a cross-functional ...

Senior Data Analyst

Overland Park, KS · On-site

$85K - $107K/yr

Strong working knowledge of web analytics and ad serving tools (Google Analytics 4, Adobe Analytics, Google Campaign Manager 360). * Strong working knowledge of SQL and cloud data warehouse ...

Senior Data Analyst

Overland Park, KS

$85K - $107K/yr

Strong working knowledge of web analytics and ad serving tools (Google Analytics 4, Adobe Analytics, Google Campaign Manager 360). * Strong working knowledge of SQL and cloud data warehouse ...

Senior Data Analyst

Overland Park, KS · On-site +1

$85K - $107K/yr

Strong working knowledge of web analytics and ad serving tools (Google Analytics 4, Adobe Analytics, Google Campaign Manager 360). * Strong working knowledge of SQL and cloud data warehouse ...

Senior Data Analyst

Overland Park, KS · On-site

$85K - $107K/yr

Strong working knowledge of web analytics and ad serving tools (Google Analytics 4, Adobe Analytics, Google Campaign Manager 360). * Strong working knowledge of SQL and cloud data warehouse ...

Data Analytics- II

Bridgewater, NJ · On-site

$50 - $52/hr

SQL (Teradata), Google Cloud Platform, Big Query, Gitlab, DESIRED SKILLS: Python, Statistics EDUCATION/CERTIFICATIONS: Bachelors or Masters in Computer Science / Data Science / Business Analytics By ...

Showing results 41-60

Data Analytics Google information

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How much do data analytics google jobs pay per hour?

As of Sep 12, 2026, the average hourly pay for data analytics google in the United States is $54.75, according to ZipRecruiter salary data. Most workers in this role earn between $43.99 and $62.02 per hour, depending on experience, location, and employer.

What are data analytics roles at Google?

Data Analytics roles at Google involve collecting, processing, and interpreting large sets of data to help inform business decisions, improve products, and solve complex problems. These professionals use statistical tools, programming languages like SQL and Python, and data visualization techniques to analyze information from various sources. They work closely with teams across the company to generate insights, create reports, and support strategic planning. Their work is crucial for driving innovation and maintaining Google's competitive edge.

What are the key skills and qualifications needed to thrive as a data analytics professional using Google tools?

To thrive as a Data Analytics professional, you need a solid background in statistics, data interpretation, and analytical problem-solving, often supported by a degree in a quantitative field. Familiarity with Google Analytics, Google Data Studio, BigQuery, and relevant certifications like the Google Data Analytics Certificate is highly valued. Strong communication, critical thinking, and the ability to translate data insights into actionable recommendations are standout soft skills. These competencies are crucial for transforming complex data into strategic business decisions and driving measurable impact.

How does a data analytics professional at Google typically collaborate with cross-functional teams?

At Google, Data Analytics professionals often work closely with product managers, engineers, UX designers, and business stakeholders to translate data findings into actionable strategies. They participate in regular meetings to align on project goals, share analytical insights, and recommend data-driven solutions. Collaboration tools and clear communication are essential, as analytics experts must present complex data in an understandable way to support decision-making across departments.

What is the difference between Data Analytics Google vs Data Analyst?

AspectData Analytics GoogleData Analyst
Required CredentialsBachelor's in related field, Google certificationsBachelor's in related field, certifications vary
Work EnvironmentTech companies, corporate settings, remote optionsVarious industries, corporate and consulting firms
Employer & Industry UsagePrimarily in tech and digital marketing sectorsBroadly across finance, healthcare, retail, and more
Common Search & ComparisonYesYes

Data Analytics Google typically refers to roles involving data analysis within Google or using Google tools, often requiring specific certifications and working in tech environments. Data Analyst is a broader role across multiple industries, with varied employers and credentials. While both focus on analyzing data to inform decisions, Data Analytics Google is more specialized within the Google ecosystem, whereas Data Analyst roles are more diverse in scope and industry.

More about Data Analytics Google jobs

What cities are hiring for Data Analytics Google jobs?

Cities with the most Data Analytics Google job openings:

What states have the most Data Analytics Google jobs?

States with the most job openings for Data Analytics Google jobs include:

What other helpful pages are available for Data Analytics Google?

Other pages related to Data Analytics Google:

Infographic showing various Data Analytics Google job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 84% Full Time, 11% Part Time, and 3% Contract. Highlights an 85% Physical, 3% Hybrid, and 12% Remote job distribution, with an average salary of $113,873 per year, or $54.7 per hour.

Customer Engineer III, Data Analytics, FSI, Google Cloud

Atlanta, GA • On-site

Google Inc.
Software Development • 10K+ employees

$110K - $132K/yr

Other

Posted 5 days ago


Google rating

8.8

Company rating: 8.8 out of 10

Based on 103 frontline employees who took The Breakroom Quiz


Job description

corporate_fare Google place New York, NY, USA ; Atlanta, GA, USA ; +7 more ; +6 more

Advanced

Experience owning outcomes and decision making, solving ambiguous problems and influencing stakeholders;deep expertise in domain.

  • Bachelor's degree or equivalent practical experience.
  • 10 years of experience with cloud native architecture in a customer-facing or support role.
  • Experience with "Big Data" technologies or concepts (e.g., analytics warehousing, data processing, data transformation, data governance, data migrations, ETL, ELT, SQL, Spark, performance or scalability optimizations, batch versus streaming).
  • Experience using programming languages (e.g., Python, Spark, SQL) to demo, prototype, or workshop with customers.
  • Experience presenting to technical stakeholders and executive leaders on cataloging, access controls, and lineage for AI and agentic applications.
Preferred qualifications:
  • Experience in technical sales or consulting in cloud computing, data analytics, and Big Data.
  • Experience with developing data warehousing, data lakes, batch/real-time event processing, streaming, data processing (ETL/ELT), data migrations, data visualization tools, and data governance on cloud native architectures.
  • Experience with architecture design, implementing, tuning, schema design, and query optimization of scalable and distributed systems.
  • Experience with cloud computing (e.g., infrastructure, storage, platforms, data) and the cloud market, engaged dynamics, and customer buying behavior.
  • Experience understanding customer requirements with the ability to break down requirements and design technical architectures.
About the job

When leading companies choose Google Cloud, it's a huge win for spreading the power of cloud computing globally. Once educational institutions, government agencies, and other businesses sign on to use Google Cloud products, you come in to facilitate making their work more productive, mobile, and collaborative. You address and deliver what is most helpful for the customer. You assist fellow sales Googlers by problem-solving key technical issues for our customers. You liaise with the product marketing management and engineering teams to stay on top of industry trends and devise enhancements to Google Cloud products.
As a Practice Customer Engineer specializing in Agentic Data Cloud, you will partner with Sales Specialist to differentiate Google Cloud and position data platform as the primary foundation for enterprise-grade Agentic workflows. You will serve as the technical authority responsible for accelerating technical wins, removing complex architectural blockers, and driving the adoption of specialized, mission-critical data and AI workloads. In this role, you will leverage deep domain expertise to design unified data foundation architectures and build production-grade prototypes and Minimum Viable Products. You will advocate Google Cloud's data suite, including BigQuery, Knowledge Catalog, and the Borderless Lakehouse demonstrating how Lakehouse scale, semantic cataloging, and automated data governance directly empower high-quality, trustworthy AI Agents.
In this role, you will bridge modern data architectures with real-time, agentic execution, enable customers to move from static analytics to autonomous, AI-driven experiences. You will collaborate with technical counterparts to shape customer cloud strategies, solve sophisticated data-engineering challenges, and provide a critical feedback loop directly to Product Engineering to influence roadmap development. Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems. Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $152000 - $221000 (USD) + 42.86% bonus target + equity + benefits
Learn more about benefits at Google .

  • Drive the technical win for complex workloads within Data Analytics to ensure rapid and successful adoption, primarily supporting the sales cycle from use case identification, technical evaluation, and through customer ramp.
  • Combine sales strategies and direct development and prototyping to provide functional, customer-tailored solutions that secure buy-in from customer domain experts.
  • Deliver critical feedback from customer engagements to Product and Engineering teams to improve architectures and solutions, working within their management systems to document, prioritize and drive resolution of customer feature requests and issues, while leveraging learnings from customer engagements to contribute to reusable solutions and assets with the Go-To-Market team.
  • Help Enterprise customers leverage industry-specific unified data foundations to power real-time, AI-driven experiences (including predictive analytics, generative AI, and agent-driven applications), with clear strategic and technical differentiated solutions that directly address technical bottlenecks.

Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents-to-be, criminal histories consistent with legal requirements, or any other basis protected by law. See also Google's EEO Policy , Know your rights: workplace discrimination is illegal , Belonging at Google , and How we hire .

Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.

Equity is granted exclusively and discretionarily by Alphabet Inc. on the basis of an agreement concluded between you and Alphabet Inc. Alphabet Inc. is your sole contractual partner with respect to equity grants. GSU grants are not guaranteed, are discretionary, are subject to approval by the Alphabet Inc. board of directors or its delegate, the terms of the relevant Alphabet Inc. stock plan, and your grant agreement. They have no impact on statutory payments. Current or past grants do not confer an acquired right.

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