Role Overview
We are looking for a Senior Data Analyst to lead analytical initiatives, design advanced reporting solutions, and deliver actionable insights that drive strategic decision-making. The ideal candidate will work closely with business leaders, data engineers, and BI teams to ensure high-quality, accurate, and timely data analysis.
Key Responsibilities
Lead the design and development of reports, dashboards, and data visualizations using Power BI, Tableau, or similar tools.
Perform deep-dive data analysis to identify business opportunities, risks, and performance drivers.
Partner with stakeholders to define KPIs, metrics, and reporting standards.
Guide junior analysts and provide mentorship on analytical best practices.
Collaborate with ETL and data engineering teams to ensure data integrity, consistency, and availability in Snowflake and other sources.
Conduct advanced SQL-based queries and optimize performance for large datasets.
Present insights and recommendations to senior leadership in a clear, concise manner.
Contribute to the design of self-service reporting frameworks for business users.
Ensure compliance with data governance, security, and privacy policies.
Stay current with emerging tools and techniques to improve analytics capabilities.
Required Skills & Qualifications
7 10 years of experience as a Data Analyst or in a similar analytical role.
Advanced expertise in SQL and working with relational and cloud data warehouses (Snowflake preferred).
Proficiency in BI tools (Power BI, Tableau, Qlik) with proven dashboard development experience.
Strong analytical and problem-solving skills with the ability to interpret complex datasets.
Solid understanding of data modeling, ETL processes, and data warehousing concepts.
Proficiency in Excel (advanced formulas, macros, pivot tables).
Excellent communication and presentation skills to interact with senior stakeholders.
Ability to manage multiple priorities and deliver high-quality insights under tight deadlines.
Nice to Have
Experience with Python or R for statistical and predictive analysis.
Knowledge of data governance and cataloging tools.
Familiarity with real-time/streaming data integration.
Exposure to machine learning concepts for advanced analytics.
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