Junior Data Analyst

The Junior Data Analyst provides foundational analytics support to enable data-driven decision-making across Operations, Finance, and Technology. This role is critical in managing the growing volume of operational, financial, and systems data generated from OMS, WMS, productivity tracking, and cloud platforms.

By handling routine data preparation, reporting, and validation tasks, the Junior Data Analyst enables senior analysts and engineers to focus on higher-value initiatives such as advanced analytics, data architecture, and optimization. This role improves execution speed, enhances data quality, and supports organizational scalability.

• Extract, clean, and validate datasets from OMS, WMS, finance, and productivity systems

• Ensure data accuracy, consistency, and completeness across sources

• Perform data reconciliation and basic quality checks

• Develop and maintain recurring operational and executive reports

• Create and update dashboards and scorecards with standardized metrics and definitions

• Support reporting requirements across Operations, Finance, and Technology teams

• Conduct basic to intermediate analysis to identify trends, anomalies, and performance gaps

• Support ad hoc data requests and business inquiries

• Translate raw data into actionable insights

• Maintain data documentation, definitions, and reporting logic

• Support enforcement of data quality standards and governance practices

• Ensure consistency in KPIs, SLAs, and reporting frameworks

• Work closely with cross-functional teams to understand business requirements

• Support senior analysts, data engineers, and stakeholders in ongoing projects

• Communicate findings clearly to both technical and non-technical audiences

• Bachelor’s Degree in Information Technology, Computer Science, Data Analytics, Statistics, Mathematics, or a related field

• 0–2 years of experience in data analysis, reporting, or a related role

• Internship or academic project experience is acceptable

• Proficiency in SQL (queries, joins, aggregations, basic optimization)

• Strong Excel or Google Sheets skills (pivot tables, formulas, data manipulation)

• Basic understanding of relational databases and data modeling

• Familiarity with BI tools (Power BI, Tableau, Looker, or equivalent)

• Ability to perform data cleaning, validation, and reconciliation

• Exposure to Python or similar scripting languages is an advantage

• Strong quantitative and analytical thinking

• Ability to convert data into meaningful insights

• High attention to detail and accuracy

• Ability to identify trends, anomalies, and issues
  Structured problem-solving approach

Business Understanding

• Basic knowledge of operational and transactional data (OMS, WMS, finance, productivity metrics)

• Understanding of KPIs, SLAs, and performance scorecards

• Ability to translate business needs into analytical outputs
• Awareness of data governance and reporting standards

• Ability to present data through clear reports and dashboards

• Strong written and verbal communication skills

• Ability to explain technical findings in simple business terms

• Open to feedback and adaptable to changing priorities