Data Analyst II, Tech
Uber
•
San Francisco, CA
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0
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Not Applicable
Posted April 4, 2026
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Responsibilities
Commitments
Responsibilities
- Duties: Build framework for analysis behind company-wide decisions relating to operations, process, and optimization.
- Collaborate across teams to document and interpret business data.
- Design, build, and maintain data pipelines to power globally scalable dashboards.
- Write queries, perform data analysis, and create data visualizations to optimize operations.
- Enable product development and improvements by leveraging user data to unlock trends and patterns.
- Develop new metrics to track user engagement and retention for internal products.
- Perform time-series analyses, hypothesis testing, and ad-hoc analyses to statistically assess relative impact and extract trends on new product launches.
- Create, improve, and automate reporting methods through an understanding of databases, data relationships, and data integrity.
- May telecommute.
- Converting business requirements to data engineering requirements, source-to-target and schema design, and pipeline scheduling and dependencies.
Commitments
May telecommute.
Not Met Priorities
What still needs stronger evidence
Requirements
- Performing scalable analysis using R or Python;
- SQL, QueryBuilder, Hive, and Presto;
- Debugging and monitoring for production services;
- Data analysis;
- Quantitative modeling, including time-series forecasting, or causal impact analyses;
- Statistical analysis, including descriptive statistics, correlation, regression, or confidence intervals;
- Developing relevant metrics and KPIs to measure performance by product teams and program teams;
- Data Visualization;
- Google Sheets;
- Converting business requirements to data engineering requirements, source-to-target and schema design, and pipeline scheduling and dependencies.
Education
- (Not required) – Employer will accept a Bachelor's degree in Engineering (any), Statistics, Information Management, Information Systems, Information Technology, Mathematics, or related field, and 4 years of experience in the job offered or in a related occupation.
Employer: Uber Technologies, Inc.
Job Title: Data Analyst II, Tech
Job Location: San Francisco, California
Job Type: Full Time
Rate of Pay: $164,403 to $197,283 per year
You will be eligible to participate in Uber's bonus program, and may be offered other types of comp. You will also be eligible for various benefits. More details can be found at the following link https://www.uber.com/careers/benefits .
Duties: Build framework for analysis behind company-wide decisions relating to operations, process, and optimization. Collaborate across teams to document and interpret business data. Design, build, and maintain data pipelines to power globally scalable dashboards. Write queries, perform data analysis, and create data visualizations to optimize operations. Enable product development and improvements by leveraging user data to unlock trends and patterns. Develop new metrics to track user engagement and retention for internal products. Perform time-series analyses, hypothesis testing, and ad-hoc analyses to statistically assess relative impact and extract trends on new product launches. Create, improve, and automate reporting methods through an understanding of databases, data relationships, and data integrity. May telecommute.
Employer will accept a Bachelor's degree in Engineering (any), Statistics, Information Management, Information Systems, Information Technology, Mathematics, or related field, and 4 years of experience in the job offered or in a related occupation.
Position Requires
Performing scalable analysis using R or Python;
SQL, QueryBuilder, Hive, and Presto;
Debugging and monitoring for production services;
Data analysis;
Quantitative modeling, including time-series forecasting, or causal impact analyses;
Statistical analysis, including descriptive statistics, correlation, regression, or confidence intervals;
Developing relevant metrics and KPIs to measure performance by product teams and program teams;
Data Visualization;
Google Sheets;
Converting business requirements to data engineering requirements, source-to-target and schema design, and pipeline scheduling and dependencies.
Job Title: Data Analyst II, Tech
Job Location: San Francisco, California
Job Type: Full Time
Rate of Pay: $164,403 to $197,283 per year
You will be eligible to participate in Uber's bonus program, and may be offered other types of comp. You will also be eligible for various benefits. More details can be found at the following link https://www.uber.com/careers/benefits .
Duties: Build framework for analysis behind company-wide decisions relating to operations, process, and optimization. Collaborate across teams to document and interpret business data. Design, build, and maintain data pipelines to power globally scalable dashboards. Write queries, perform data analysis, and create data visualizations to optimize operations. Enable product development and improvements by leveraging user data to unlock trends and patterns. Develop new metrics to track user engagement and retention for internal products. Perform time-series analyses, hypothesis testing, and ad-hoc analyses to statistically assess relative impact and extract trends on new product launches. Create, improve, and automate reporting methods through an understanding of databases, data relationships, and data integrity. May telecommute.
Employer will accept a Bachelor's degree in Engineering (any), Statistics, Information Management, Information Systems, Information Technology, Mathematics, or related field, and 4 years of experience in the job offered or in a related occupation.
Position Requires
Performing scalable analysis using R or Python;
SQL, QueryBuilder, Hive, and Presto;
Debugging and monitoring for production services;
Data analysis;
Quantitative modeling, including time-series forecasting, or causal impact analyses;
Statistical analysis, including descriptive statistics, correlation, regression, or confidence intervals;
Developing relevant metrics and KPIs to measure performance by product teams and program teams;
Data Visualization;
Google Sheets;
Converting business requirements to data engineering requirements, source-to-target and schema design, and pipeline scheduling and dependencies.