Key Responsibilities
- Collect, clean, validate, and analyze data from multiple sources.
- Identify trends, patterns, and insights that support business objectives.
- Develop and maintain reports, dashboards, and data visualizations.
- Write SQL queries to extract and transform data from databases.
- Prepare recurring and ad-hoc reports for business stakeholders.
- Monitor key performance indicators (KPIs) and identify significant changes or trends.
- Perform data quality checks and resolve data inconsistencies.
- Work closely with business, product, finance, marketing, and technology teams to understand analytical requirements.
- Translate business questions into analytical approaches and actionable insights.
- Present findings and recommendations to technical and non-technical stakeholders.
- Automate repetitive reporting and data-processing tasks where possible.
- Maintain documentation for reports, dashboards, datasets, and analytical processes.
Required Qualifications
- Bachelor’s degree in Statistics, Mathematics, Economics, Computer Science, Business Analytics, Engineering, or a related field.
- Strong proficiency in SQL.
- Advanced knowledge of Microsoft Excel, including PivotTables, XLOOKUP/VLOOKUP, formulas, and data analysis.
- Experience with data visualization and BI tools such as Power BI or Tableau.
- Good understanding of descriptive statistics and analytical concepts.
- Strong attention to detail and data-quality mindset.
- Excellent problem-solving and communication skills.
Preferred Qualifications
- Experience with Python or R for data analysis.
- Knowledge of Pandas, NumPy, or other analytics libraries.
- Experience working with large datasets.
- Familiarity with databases such as PostgreSQL, MySQL, SQL Server, or Oracle.
- Understanding of ETL/ELT concepts and data pipelines.
- Experience with cloud data platforms such as AWS, Azure, or Google Cloud.
- Knowledge of A/B testing and basic statistical analysis.
- Experience with data warehouses such as Snowflake, BigQuery, or Redshift.
Technical Skills
Database & Querying: SQL, PostgreSQL, MySQL, SQL Server, Oracle
Analytics: Excel, Python, R
Visualization: Power BI, Tableau, Excel
Python Libraries: Pandas, NumPy, Matplotlib, Seaborn
Cloud/Data Platforms: AWS, Azure, GCP, Snowflake, BigQuery
- Tools: Git, Jupyter, Jira/Confluence
