Data Analyst

Key Responsibilities

• Collect, clean, transform, and analyze large and complex datasets from multiple sources.
• Write optimized and complex SQL queries for data extraction, transformation, aggregation, and analysis.
• Use Python for data analysis, automation, statistical analysis, and data processing.
• Work with GCP services such as BigQuery, Cloud Storage (GCS), and other relevant cloud data services.
• Develop and maintain analytical datasets, data models, and reporting solutions.
• Identify trends, patterns, anomalies, and business opportunities from data.
• Build dashboards, reports, and visualizations using tools such as Looker, Looker Studio, Power BI, or Tableau.
• Perform data validation and quality checks to ensure accuracy and consistency.
• Automate repetitive reporting and data-processing activities using Python and SQL.
• Collaborate with business stakeholders, data engineers, product teams, and other technical teams to understand analytical requirements.
• Translate business requirements into data queries, analytical solutions, and actionable insights.
• Monitor key performance indicators (KPIs) and provide regular analytical reports.
• Support ad-hoc analysis and provide data-driven recommendations to stakeholders.
• Document data sources, analytical processes, queries, and reporting logic.

Required Skills

• Strong proficiency in SQL for data extraction, analysis, joins, CTEs, and window functions.
• Good hands-on experience with Python, especially Pandas and NumPy, for data analysis and automation.
• Experience with GCP, particularly BigQuery and Google Cloud Storage (GCS).
• Knowledge of data cleaning, transformation, validation, and visualization.
• Experience with BI tools such as Looker, Power BI, or Tableau.
• Understanding of data warehousing and ETL/ELT concepts.
• Strong analytical, problem-solving, and communication skills.