Description :

Role Overview :

As a Senior Data Analyst, you will lead data analysis initiatives, design analytical models, and support strategic decision-making through data-driven insights.

You will collaborate closely with cross-functional teamsincluding product, marketing, finance, engineering, and operationsto understand business challenges and provide analytical solutions.

Key Responsibilities :

- Analyze large datasets from multiple sources to identify trends, patterns, and insights.

- Build dashboards, reports, and visualizations to support KPIs, OKRs, and business performance tracking.

- Conduct deep-dive analysis for problem-solving and strategic planning.

- Translate complex data findings into clear, actionable recommendations for leadership.

- Develop and maintain scalable data models, pipelines, and ETL processes.

- Ensure data accuracy, integrity, and consistency across all data sources.

- Collaborate with data engineering teams to improve data architecture and data warehouse design.

- Perform statistical and predictive modeling using advanced analytics techniques.

- Partner with business leaders to define analytics requirements and metrics.

- Lead analytical projects end-to-end, including scoping, data extraction, analysis, and presentation.

- Provide mentorship and guidance to junior analysts on best practices and analytical approaches.

- Present findings to senior management and influence key strategic decisions.

- Use BI/reporting tools such as Tableau, Power BI, Looker, or Qlik to create dashboards and visualizations.

- Utilize SQL for advanced data interrogation and manipulation.

- Employ Python or R for statistical analysis, data modeling, and automation.

- Work with cloud data platforms (AWS, GCP, Azure), data warehouses like Snowflake, BigQuery, or Redshift.

Required Qualifications :

- Bachelor's or Masters degree in Data Science, Statistics, Mathematics, Computer Science, Economics, or related field.

- 4 to 6+ years of experience in data analysis or business analytics.

- Expert-level proficiency in SQL and strong experience with data warehouses.

- Strong analytical thinking, statistical knowledge, and problem-solving abilities.

- Experience with data visualization tools (Tableau, Power BI, Looker, etc.

- Hands-on experience with Python or R for analysis and modeling.

- Strong understanding of A/B testing, forecasting, experiment design, and statistical modeling.

- Ability to manage multiple projects simultaneously in a fast-paced environment.

- Excellent communication skills with the ability to present insights to non-technical stakeholders