Senior Data Analyst

We are looking for a Senior Data Analyst to transform complex data into actionable insights that support business and product decisions. The ideal candidate will have strong analytical skills, excellent SQL expertise, and experience working with large datasets, dashboards, and business stakeholders. The role requires a combination of data analysis, business understanding, problem-solving, and storytelling to identify trends, measure performance, and provide recommendations that drive business outcomes.

Responsibilities:

• Analyze large and complex datasets to identify trends, patterns, opportunities, and business insights.
• Work closely with product, engineering, business, and other stakeholders to understand analytical requirements and translate them into data-driven solutions.
• Develop and maintain dashboards, reports, and data visualizations to track key business and product metrics.
• Write complex and optimized SQL queries to extract, transform, and analyze data from multiple sources.
• Define and monitor KPIs and business metrics and ensure consistency and accuracy across reporting.
• Perform ad hoc analysis and deep dives to support business decisions and strategic initiatives.
• Identify data quality issues, investigate root causes, and work with relevant teams to resolve them.
• Conduct trend analysis, cohort analysis, segmentation, funnel analysis, and root-cause analysis.
• Collaborate with data engineering teams to improve data availability, data models, and analytical datasets.
• Present findings and recommendations to stakeholders through clear data storytelling and visualizations.
• Automate recurring reports and analytical processes to improve efficiency and reduce manual effort.
• Support A/B testing, experimentation, and statistical analysis where required.
• Establish and follow best practices for data analysis, documentation, reporting, and data quality.
• Mentor junior analysts and contribute to improving the team's analytical capabilities.

Requirements:

• 4-7 years of experience in data analytics, business intelligence, product analytics, or a related field.
• Strong proficiency in SQL, including complex joins, subqueries, CTEs, window functions, and query optimization.
• Strong experience with Python or R for data analysis and automation.
• Hands-on experience with BI and visualization tools such as Tableau, Power BI, Looker, or equivalent.
• Strong understanding of statistics, data analysis, and analytical methodologies.
• Experience working with large datasets and databases.
• Strong understanding of data modeling and data warehouse concepts.
• Ability to translate business problems into analytical questions and actionable insights.
• Strong problem-solving and critical-thinking skills.
• Excellent communication and stakeholder-management skills.
• Ability to independently manage multiple analytical projects and deliver within timelines.

Good to Have:

• Experience in product analytics within a SaaS or technology product company.
• Experience with A/B testing, experimentation, hypothesis testing, and statistical modeling.
• Knowledge of cloud data platforms such as AWS, Snowflake, BigQuery, Redshift, or Databricks.
• Experience working with Spark/PySpark or other distributed data-processing technologies.
• Exposure to machine learning, predictive analytics, or AI/GenAI use cases.
• Experience working with modern data stack tools such as dbt or Airflow.
• Experience defining and maintaining enterprise-level data/KPI standards.