Senior Data Analyst
New
P
PairedEcommerce DTC
Open to candidates based in Europe, European/Israel working hoursFull-TimeSenior
Salary not disclosed
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Job Details
- Languages
- English
- Experience
- 5+ years
- Required Skills
- SQLSnowflakeTableauBigQueryRedshiftLooker
Requirements
- 5+ years of hands-on experience in Marketing Analytics, Growth Analytics, Product Analytics, or Performance Analytics
- Strong experience supporting ecommerce, DTC, B2C, or consumer-focused businesses
- Advanced SQL proficiency, including joins, window functions, cohort logic, attribution analysis, and large dataset querying
- Experience working directly with warehouse-based analytics environments such as BigQuery, Snowflake, Redshift, or similar
- Experience with BI and visualization platforms such as Looker, Tableau, or Looker Studio
- Strong understanding of ecommerce unit economics, including CAC, ROAS, MER, LTV, payback periods, contribution margin, and funnel performance
- Experience partnering with Paid Media, Growth, or Marketing teams on performance analysis and optimization
- Demonstrated ownership of analytical initiatives with measurable business impact
- Comfortable operating independently in ambiguous, fast-paced environments
- Practical experience using AI tools such as ChatGPT, Claude, Cursor, Copilot, or similar within analytics workflows
- Strong written and verbal English communication skills
Responsibilities
- Analyze revenue, contribution margin, CAC, LTV, refund behavior, and acquisition efficiency across channels and geographies
- Partner closely with Growth and Paid Media teams to evaluate channel performance and budget allocation
- Build cohort analyses, funnel analyses, attribution logic, and performance monitoring frameworks
- Identify revenue leakage, operational inefficiencies, and growth opportunities through deep analysis
- Translate complex datasets into clear business recommendations for leadership
- Build scalable reporting and KPI frameworks on top of a modern warehouse environment
- Support forecasting, anomaly detection, experimentation analysis, and decision support initiatives
- Collaborate with Data Engineering to improve data quality, modeling, and infrastructure
- Leverage AI-powered workflows and tooling to accelerate analytics, SQL development, documentation, and operational efficiency
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