Data Analyst
Experience: 4 - 20 years
Max Experience: 20
The candidate should be comfortable working with large datasets, developing dashboards, automating reports, and presenting insights to business stakeholders.
Key Responsibilities
Collect, clean, validate, and analyze large datasets from multiple sources.
Write complex SQL queries to extract, transform, and analyze data.
Build and maintain interactive dashboards and reports using Power BI, Tableau, or similar BI tools.
Perform exploratory data analysis (EDA) to identify trends, patterns, anomalies, and business opportunities.
Translate business requirements into analytical solutions, KPIs, and meaningful reports.
Develop automated reporting workflows to reduce manual effort and improve reporting accuracy.
Collaborate with business, product, engineering, finance, and operations teams to understand analytical requirements.
Monitor business performance through metrics, dashboards, and periodic reporting.
Ensure data quality, consistency, accuracy, and integrity across reporting systems.
Present findings and recommendations clearly to technical and non-technical stakeholders.
Document data definitions, analytical methodologies, reporting logic, and business metrics.
Identify opportunities to improve data processes, reporting efficiency, and analytical practices.
Required Skills And Qualifications
Bachelor's degree in Computer Science, Statistics, Mathematics, Economics, Engineering, or a related field.
3–6 years of relevant experience in data analytics, business intelligence, or reporting.
Strong proficiency in SQL, including joins, subqueries, CTEs, window functions, and aggregations.
Hands-on experience with Power BI, Tableau, or another business intelligence platform.
Strong Excel skills, including pivot tables, lookup functions, conditional formulas, and data analysis.
Working knowledge of Python for data analysis using Pandas and NumPy is preferred.
Understanding of data cleaning, data validation, exploratory analysis, and statistical concepts.
Experience defining and tracking KPIs, metrics, and business performance indicators.
Strong analytical thinking, problem-solving, and attention to detail.
Excellent communication and presentation skills.
Preferred Qualifications
Experience working with cloud data platforms such as AWS, Azure, or Google Cloud.
Familiarity with data warehouses such as Snowflake, BigQuery, Redshift, or similar platforms.
Exposure to ETL/ELT pipelines and data transformation tools.
Knowledge of statistical analysis, hypothesis testing, and A/B testing.
Experience working in a product-based company, startup, or fast-paced business environment.
Understanding of data modeling, dimensional modeling, and database optimization.
Experience automating
ChatGPT is AI and can make mistakes.