Uber Hiring: Data Analyst II, Tech 2026:-
Uber is hiring for the position of Data Analyst II, Tech in Hyderabad, Telangana, India. This opportunity is part of the Legal organisation, specifically the Compliance & Ethics subteam, and focuses on data analytics, advanced SQL, data quality, regulatory reporting, data privacy, and scalable data-sharing solutions.
Complete job details are provided below.
| Company: | Uber |
| Job Title: | Data Analyst II, Tech |
| Team: | Legal |
| Subteam: | Compliance & Ethics |
| Location: | Hyderabad, India |
| Experience Required: | 4+ years in data analytics |
About the Company:-
Uber is a global technology company that connects people with transportation, delivery, and other services through its digital platform.
The company uses technology, data, and analytics to support business operations, improve platform experiences, and make informed decisions. Its teams work across engineering, operations, legal, compliance, public policy, and other business functions.
Uber emphasises collaboration, innovation, accountability, and the use of data to solve complex operational and regulatory challenges.
Role Overview:-
Uber is seeking a technically skilled and motivated Data Analyst II, Tech to join its Data Engineering and Sharing Solutions Team, specialising in Ethics Compliance & Security data.
The role involves building and refining SQL transformations, defining data quality frameworks, and supporting data-sharing solutions that help operational teams respond to law enforcement and regulatory requests.
The selected candidate will act as a technical bridge between data engineering teams and business stakeholders, particularly Legal and Public Policy teams. The role requires translating complex and sometimes ambiguous regulatory requirements into accurate technical specifications and scalable analytical solutions.
A key focus is ensuring that compliance and safety datasets are accurate, consistent, privacy-conscious, and ready for audits and external regulatory use.
Educational Requirements:-
Candidates should possess one of the following qualifications:
- Bachelor of Technology (B.Tech).
- Bachelor of Engineering (B.E.).
- Equivalent degree in a quantitative field, such as Statistics or Computer Science.
Candidates should also have relevant professional experience in data analytics, logic building, and data modelling.
Preferred domain background: Compliance, Risk, or Public Safety within FinTech, InsurTech, or a similar high-stakes environment.
Key Skills:-
1. Technical Skills
- Advanced SQL Programming
- Common Table Expressions (CTEs)
- SQL Window Functions
- Complex Database Queries
- SQL Transformations
- Query Optimisation
- Data Modelling
- Business Logic Development
- Data Quality Frameworks
- Automated Data Validation
- Exception Reporting
- Data Reconciliation
- Data Integrity Management
- Data Transformation and Processing
- Analytical Solution Design
2. Data Quality and Governance Skills
- Data Quality (DQ) Standards
- Data Validation Rules
- Data Consistency and Accuracy
- Data Integrity Checks
- Data Quality Monitoring
- Root Cause Analysis
- Data Remediation
- Audit-Ready Dataset Preparation
- Reporting Logic Standardisation
- Single Source of Truth Development
- Data Documentation
- Quality Assurance for Compliance Data
3. Data Privacy and Compliance Skills
- Data Privacy Principles
- Personally Identifiable Information (PII) Handling
- Data Redaction
- Sensitive Data Protection
- Regulatory Reporting Requirements
- Compliance Data Management
- Ethics and Security Data
- Law Enforcement Data Requests
- Audit Readiness
- Risk and Compliance Analytics
- Data Sharing Controls
4. Data Analytics and Modelling Skills
- Data Analytics
- Business Logic Building
- Data Modelling
- Analytical Problem-Solving
- Data Interpretation
- Reporting Logic Development
- Modular Data Solutions
- Self-Service Data Products
- Data Request Pattern Analysis
- Scalable Analytical Workflows
- Business Requirements Analysis
5. Solution Design and Data Engineering Collaboration
- Data-Sharing Solution Design
- Data Engineering Collaboration
- Technical Requirements Gathering
- Scalable Data Workflows
- Reusable SQL Logic
- Workflow Automation
- Technical Documentation
- Cross-Functional Consultation
- Data Product Development
- Process Improvement
6. Soft Skills
- Strong analytical thinking
- Attention to detail
- Problem-solving abilities
- Technical communication
- Stakeholder management
- Cross-functional collaboration
- Requirement analysis
- Ability to interpret ambiguous requirements
- Documentation skills
- Ownership and accountability
- Ability to work in high-stakes environments
Roles and Responsibilities:-
1. SQL Development and Reporting Logic
- Develop and refine SQL transformations used across compliance and safety datasets.
- Build business logic that serves as a single source of truth for reporting and analytical outputs.
- Write complex SQL queries using CTEs and window functions.
- Query multi-layered databases and transform raw data into reliable analytical datasets.
- Optimise SQL logic to improve query performance and maintainability.
- Standardise reporting calculations and business rules across data products.
- Ensure that reporting outputs align with defined business and regulatory requirements.
2. Data Quality Management
- Define and implement data quality standards for compliance and safety datasets.
- Develop automated validation frameworks and data quality scripts.
- Create validation rules to identify inaccurate, incomplete, inconsistent, or invalid records.
- Build exception reporting mechanisms to highlight data quality issues.
- Investigate recurring data inconsistencies and perform root cause analysis.
- Coordinate remediation activities to resolve data defects.
- Verify data integrity before information is shared with external regulators.
- Ensure datasets remain accurate, consistent, and audit-ready.
3. Regulatory Data-Sharing Solutions
- Assist in designing scalable data-sharing frameworks for regulatory and law enforcement requests.
- Collaborate with data engineering teams to develop solutions for operational data requests.
- Translate regulatory requirements into precise technical specifications.
- Help establish repeatable workflows for processing data-sharing requests.
- Support the development of modular solutions that can handle recurring requests efficiently.
- Ensure data-sharing processes follow applicable requirements and established controls.
- Help operational teams fulfil requests accurately and consistently.
4. Legal and Public Policy Collaboration
- Serve as a key analytical contact for Legal and Public Policy teams.
- Understand business, legal, and regulatory requirements related to compliance data.
- Convert complex or ambiguous requirements into actionable analytical logic.
- Work with stakeholders to clarify data definitions, reporting needs, and validation rules.
- Communicate technical findings and limitations to non-technical stakeholders.
- Coordinate with cross-functional teams to ensure data solutions meet operational needs.
- Support the delivery of accurate and consistent information for compliance activities.
5. Data Privacy and Sensitive Information Handling
- Apply data privacy principles when working with sensitive compliance and safety datasets.
- Understand the technical requirements of handling personally identifiable information (PII).
- Support appropriate data redaction processes where required.
- Help ensure sensitive data is handled according to applicable requirements and approved procedures.
- Consider privacy implications when designing data transformations and sharing workflows.
- Maintain a privacy-conscious approach to data access, preparation, and reporting.
6. Scalable Analytical Solutions
- Identify recurring patterns in data requests and operational reporting needs.
- Develop modular SQL logic and reusable analytical workflows.
- Build technical documentation that supports repeatable execution.
- Enable other teams to use self-service data products and standardised logic.
- Reduce repetitive manual work by improving workflow scalability.
- Promote maintainable solutions that support increasing request volumes.
- Help improve efficiency and consistency across compliance data operations.
7. Documentation and Process Improvement
- Document SQL transformations, business rules, data quality checks, and reporting logic.
- Maintain technical specifications for reusable analytical components.
- Record validation requirements and exception-handling processes.
- Identify opportunities to improve data quality and reporting workflows.
- Collaborate with engineering and business teams to implement sustainable improvements.
- Support knowledge sharing and consistent execution across teams.
Essential Skills and Experience:-
Candidates must demonstrate the following qualifications and experience:
- 4+ years of experience in data analytics, particularly logic building and data modelling.
- B.Tech, B.E., or an equivalent degree in a quantitative field.
- Advanced SQL skills, including CTEs, window functions, and optimised data transformations.
- Experience defining data quality validation rules and exception reporting.
- Experience producing accurate, audit-ready datasets.
- Experience designing self-service data products or reusable analytical logic.
- Strong understanding of data privacy, PII handling, and data redaction.
- Ability to translate business and regulatory requirements into technical solutions.
Preferred experience: Compliance, Risk, or Public Safety within FinTech, InsurTech, or another high-stakes environment.
Eligibility Criteria:-
- Must have at least 4 years of relevant data analytics experience.
- Must possess a B.Tech, B.E., or equivalent quantitative qualification.
- Must have strong SQL knowledge and experience with complex queries.
- Must understand data modelling and business logic development.
- Must have experience with data quality frameworks, validation rules, and exception reporting.
- Must be capable of developing reliable and audit-ready analytical datasets.
- Must understand data privacy principles, PII handling, and data redaction.
- Must be able to work with technical and non-technical stakeholders.
- Must demonstrate strong analytical, documentation, and problem-solving skills.
- A background in compliance, risk, public safety, or a similar regulated environment is preferred.
Uber Hiring: Data Analyst II, Tech 2026 Application Process:-
Interested candidates can apply from the given below link.
Apply Link:- Click Here To Apply
Note:- Only the shortlisted candidates will be notified for the further interview process.
