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
Robust proficiency in SQL for data extraction, analysis, joins, CTEs, and window functions.
Valuable 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.
Robust analytical, problem-solving, and communication skills.

📌 Data Analyst Noida
🏢 Innodata India
📍 Noida