What are the responsibilities and job description for the Data Analyst position at Scale.jobs?
About The Role
The Data Analyst translates complex raw datasets into actionable business intelligence, bridging the gap between raw data infrastructure and executive decision-making. The role focuses on building scalable reporting frameworks and identifying trends within user behavior, product performance, and operational efficiency.
The role works closely with data engineers to refine data modeling requirements and with product managers to define KPIs that drive the product roadmap. This position is critical for maintaining data integrity and fostering a culture of data-driven experimentation across the organization.
Key Responsibilities
The Data Analyst translates complex raw datasets into actionable business intelligence, bridging the gap between raw data infrastructure and executive decision-making. The role focuses on building scalable reporting frameworks and identifying trends within user behavior, product performance, and operational efficiency.
The role works closely with data engineers to refine data modeling requirements and with product managers to define KPIs that drive the product roadmap. This position is critical for maintaining data integrity and fostering a culture of data-driven experimentation across the organization.
Key Responsibilities
- Develop and maintain automated Looker or Tableau dashboards that provide real-time visibility into core business KPIs and product health metrics
- Write complex, optimized SQL queries to extract and aggregate data from Snowflake or BigQuery data warehouses for ad-hoc analysis and deep-dives
- Perform statistical analysis to evaluate the results of A/B tests, providing clear recommendations on product feature launches and marketing spend
- Partner with data engineering to design and document dbt models, ensuring the analytics layer is clean, performant, and reliable
- Identify data quality issues or anomalies within internal tracking systems and collaborate with technical teams to resolve upstream instrumentation gaps
- Present data findings and strategic insights to non-technical stakeholders through clear visualizations and structured executive summaries
- 2–4 years of experience in data analytics, business intelligence, or a similar quantitative role within a technology company
- Advanced proficiency in SQL, including window functions, complex joins, and query optimization techniques
- Proven experience building production-grade dashboards using BI tools such as Looker, Tableau, or PowerBI
- Solid understanding of basic statistics, including hypothesis testing, probability distributions, and correlation analysis
- Experience working with modern data stack tools such as dbt, Snowflake, or BigQuery
- Bachelor’s degree in Mathematics, Statistics, Computer Science, Economics, or a related quantitative field
- Bonus: Proficiency in Python or R for data manipulation (pandas, NumPy) and experience with version control systems like Git