Junior Data Analyst

About the Role

Business Intelligence and Reporting

• Prepare recurring daily, weekly, and monthly reports covering revenue, trip activity, fleet utilization, customer acquisition, and operational efficiency.
• Develop, maintain, and improve interactive Tableau dashboards for management and operational teams.
• Monitor KPIs, investigate unexpected changes, and identify potential performance issues.
• Prepare accurate datasets, summaries, and preliminary insights for management reporting.
• Standardize metric definitions and documentation for consistent reporting.

Data Analysis and Insights

• Analyze customer behavior, fleet performance, productivity, and operational trends.
• Conduct ad hoc analyses and collaborate across departments.
• Identify trends, anomalies, correlations, and potential business improvement opportunities.
• Assist with forecasting, customer segmentation, retention analysis, and other analytical projects.
• Present findings clearly and explain their business implications.

SQL, Data Quality, and Automation

• Write and optimize SQL queries to extract, join, aggregate, and analyze data from relational databases.
• Validate data accuracy, identify inconsistencies, and investigate discrepancies between data sources.
• Maintain reusable queries, reporting datasets, and documented business logic; apply data-cleaning, transformation, and reconciliation techniques.
• Identify repetitive reporting tasks for automation and develop or maintain basic workflows using SQL, Python, Excel, or other suitable tools.
• Support reporting refreshes and analytical pipelines; document workflows, dependencies, and validation checks.

Analytics Infrastructure

• Support analytical data models, centralized datasets, and data warehousing initiatives.
• Assist with SQL transformations, data reconciliation, pipeline testing, and documentation.
• Collaborate with the technical team to improve data accessibility, quality, and reporting performance.
• Contribute to scalable, reusable analytical datasets.

Required Qualifications and Skills

• Bachelor's degree in Data Analytics, Computer Science, Statistics, Mathematics, Economics, Engineering, or a related quantitative field.
• 0–2 years of relevant experience, including internships, academic projects, or equivalent practical experience.
• Working knowledge of SQL, including joins, aggregations, subqueries, and common table expressions.
• Proficiency in Microsoft Excel, including PivotTables, lookup functions, and data analysis.
• Working knowledge of at least one analytics or visualization tool, preferably Tableau or Power BI.
• Basic Python proficiency for data analysis or automation, or demonstrated ability to learn it.
• Strong analytical reasoning, problem-solving, attention to detail, communication, and willingness to learn.

Preferred Qualifications

• Experience with PostgreSQL or similar relational databases; familiarity with pandas and NumPy; or knowledge of SQL window functions and basic query optimization.
• Exposure to data modelling, ETL/ELT processes, automated pipelines, cloud data warehouses such as Snowflake, BigQuery, or ClickHouse, Git, APIs, or scheduled data workflows.
• Knowledge of statistical analysis, forecasting, or customer analytics; exposure to mobility, transportation, automotive, subscription, or consumer-platform businesses. These qualifications are advantageous, not mandatory.