W2|| Data Analyst

Title:  Data Analyst

Location: Torrance, CA (Hybrid)

Interview: Skype
Duration: 6+ months 

Job Description - 

Requirements
- Bachelor''s degree in Data Science, Computer Science, Information Systems, Engineering, or a related field.
- 5+ 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).
- Provide support to 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.