Transforms complex datasets into strategic insights supporting revenue growth and executive decision-making. Responsibilities include defining KPIs, building analytical models, creating dashboards and reports, analyzing customer behavior and revenue, identifying risks and opportunities, conducting cohort, retention, funnel, and forecasting analyses, and partnering with business stakeholders and data engineering teams.
Senior Data Analyst
Summary
We are seeking a commercially driven and highly analytical Senior Data Analyst to transform intricate datasets into strategic insights that fuel decision-making and revenue growth. This pivotal position serves as the critical link between business stakeholders and data engineering teams, guaranteeing that data assets are accurate, robustly modeled, and primed for immediate use. The successful candidate will possess a unique blend of advanced SQL proficiency, sharp business intuition, and compelling storytelling capabilities, backed by practical experience utilizing contemporary cloud-based data ecosystems.
Responsibilities
- Convert complex business challenges into structured analytical models and define quantifiable key performance indicators.
- Design and deploy interactive dashboards and high-level reports tailored for executive leadership.
- Conduct comprehensive investigative analysis spanning customer behavior, revenue streams, product performance, and operational efficiency.
- Detect emerging patterns, potential risks, and strategic opportunities within the data landscape.
- Execute sophisticated analytical techniques, including cohort studies, retention tracking, funnel optimization, and predictive forecasting.
- Architect and construct analytical data models to support advanced querying and reporting needs.
Requirements
Requirements
- Proven expertise in SQL for complex data extraction and manipulation.
- Strong commercial acumen with the ability to align data insights with business objectives.
- Exceptional data storytelling skills to communicate findings effectively to non-technical audiences.
- Hands-on experience working with modern cloud data platforms.
- Demonstrated ability to bridge the gap between technical data engineering and business strategy.
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