Growth Data Analyst

Responsibilities

1. Design, develop, and maintain interactive dashboards in Tableau to support both recurring and ad-hoc reporting needs across various growth functions and leadership teams, enabling real-time performance tracking and insights.
2. Write and optimize complex SQL queries on Databricks to drive business growth in user acquisition, campaign ROI, and customer lifecycle management.
3. Partner with cross-functional teams—including growth, product, data engineering, and external vendors—to improve data infrastructure, independently troubleshoot pipeline issues, and ensuring accurate, scalable, and efficient data pipelines that support business goals.
4. Streamline and automate recurring data workflows and processes, manage SQL automation and job scheduling, and maintain thorough documentation to enhance team productivity and data reliability.
5. Develop analytical models to inform marketing strategies, including predictive LTV, lead scoring or marketing mix modeling, providing actionable insights for campaign planning and optimization.
6. Leverage statistical techniques and business intelligence tools to uncover trends, patterns, and opportunities that inform strategic growth decisions.
7. Collaborate closely with cross-functional stakeholders to implement data-driven solutions and support end-to-end project delivery, ensuring alignment with business objectives and timelines.
8. Stay proactive in professional development by exploring emerging AI tools and methodologies in data science and marketing analytics, continuously enhancing analytical capabilities and industry knowledge.

Requirements

1. Bachelor's degree in a quantitative field such as Computer Science, Statistics, Engineering, Information Systems, or related fields.
2. 2+ years of experience in data analysis or a related field. Experience in the Crypto and Technology industry is a plus.
3. Proficiency in SQL, Databricks, and Tableau for processing, analyzing, and visualizing large datasets.
4. Experience with statistical software (e.g., R, Python) and libraries for managing, manipulating, and analyzing data.
5. Strong analytical skills with the ability to collect, organize, analyze, and disseminate significant amounts of information with attention to detail and accuracy.
6. Adept at querying, report writing, and presenting findings.
7. Understanding of digital marketing concepts, such as user acquisition (organic, non-organic, partnerships, etc.), campaign management, and customer lifecycle management.
8. Familiarity with tools like AppsFlyer, Google Tag Manager, Google Analytics, and SensorTower.
9. Strong communication skills to effectively convey complex data insights to non-technical stakeholders and to translate business needs into technical and data requirements.
10. Ability to thrive in a fast-paced environment, manage multiple projects, and adapt to shifting priorities.