Data Analyst
Role Overview
Mid-level individual contributor who owns smaller analytical domains end-to-end and develops toward senior-level independence.
Works with business stakeholders and data, analytics, and engineering colleagues.
Key Skills for This Role
Full Job Posting
Role summary
Mid-level individual contributor who owns smaller analytical domains end-to-end and develops toward senior-level independence.
Works with business stakeholders and data, analytics, and engineering colleagues.
Analytics and experimentation
- Scopes, analyzes, presents, and follows through on analytical work for assigned business areas.
- Provides interpretive ad hoc analysis for Marketing, Product, Finance, and Account Management.
- Proactively surfaces trends and anomalies; supports A/B test preparation, tracking, and results summaries.
BI and data quality
- Builds and maintains Looker dashboards and Explores and develops documented LookML.
- Contributes to the semantic layer, identifies metric inconsistencies, and expands self-service analytics.
- Investigates data discrepancies and escalates upstream issues with evidence; collaborates on SQL optimization and derived table design.
- Diagnoses dashboard freshness and quality issues and maintains accuracy as warehouse structures evolve.
Collaboration and AI-enabled analytics
- Contributes to coding standards, documentation, and code reviews; supports junior analysts under senior guidance.
- Uses AI and LLM tools for SQL, LookML, documentation, and exploratory analysis; experiments with assisted insight narration and anomaly detection.
- Partners with senior analysts, data engineers, analytics engineers, and business stakeholders.
Required qualifications
- Bachelor’s degree in a quantitative field or equivalent practical experience.
- 2–4 years in data analytics or BI; strong SQL including window functions and CTEs.
- At least 2 years of hands-on Looker and LookML development.
- Experience with AWS or Google Cloud data warehouses, including Redshift or BigQuery.
- Experience building dashboards and Explores for non-technical business users.
- Working knowledge of Git, pull request reviews, code style guides, and Agile development.
- Ability to translate business questions into analytical tasks; the source text is truncated after this requirement begins.
Development areas
- The posting describes ongoing skill development across advanced SQL, Python, statistical analysis, and cloud data platforms.
- The posting describes building toward independent ownership of experimentation, GA4, and stakeholder advisory.
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