About the Role:

We are looking for a Data Analyst with deep expertise in data analysis, complex SQL queries, and data validation within a data warehouse environment. The ideal candidate is analytical, detail-oriented, and passionate about turning raw data into clear insights that support business decisions. Experience with PySpark and Airflow is a strong plus but not mandatory.

Key Responsibilities:

• Create and optimize complex SQL queries across large datasets to support ad hoc and recurring analysis needs.
• Perform in-depth data analysis to identify trends, patterns, and anomalies across structured and semi-structured datasets.
• Conduct rigorous data validation to ensure data integrity and accuracy across the data warehouse and analytical reports.
• Translate business questions into analytical solutions with actionable insights.
• Partner with data engineering teams to understand data sources, schemas, and ensure data is modeled for optimal analysis.
• Profile new data sources and document data lineage, definitions, and business rules.
• Proactively identify data quality issues and collaborate on solutions.

Required Skills & Experience:

• 7+ years of experience in data analysis
• Advanced SQL skills, including writing complex joins, window functions, aggregations, and performance tuning.
• Strong background in data validation, reconciliation, and root-cause analysis of data discrepancies.
• Experience working with large datasets in a data warehouse environment (e.g., Redshift, Snowflake, BigQuery).
• Proven ability to gather and refine business requirements and turn them into meaningful analysis.