About the job

• Role Description We are seeking an analytical, detail-oriented, and data-driven Business Intelligence Analyst / BI Analyst / Reporting Specialist to turn complex operational and transactional datasets into actionable business insights. In this mid-level role, you will report directly to the Head of Analytics or Finance/Operations Manager and work closely with Data Engineering, Product, Finance, and Business Unit Leaders. You will be responsible for designing automated dashboards, creating key performance indicator (KPI) tracking frameworks, and synthesizing cross-departmental data into executive summaries. Responsibilities include building and maintaining data visualization models, writing optimized database queries, auditing raw data integrity across internal systems, performing root-cause variance analyses, and presenting findings to non-technical stakeholders to drive informed decision-making. Success in this position requires a strong technical proficiency in SQL and data modeling, expert-level spreadsheet capabilities, hands-on experience with modern BI platforms, and the ability to translate complex numerical metrics into compelling executive narratives.QualificationsEducation: Bachelor's degree in Business Analytics, Data Science, Statistics, Computer Science, Finance, Information Systems, or a related quantitative field.
• BI & Data Visualization Tools: 2+ years of hands-on experience building interactive reports, dashboards, and semantic data models in platforms such as Power BI, Tableau, Looker, or Qlik Sense.
• Database Management & SQL: Advanced SQL querying skills (joins, CTEs, window functions, query optimization) across relational databases (e.g., PostgreSQL, MySQL, MS SQL Server, Snowflake, or BigQuery).
• Data Extraction & ETL Workflows: Practical understanding of data warehousing concepts, ETL/ELT pipelines, data hygiene, and automated scheduled refreshes.
• Spreadsheet Modeling & Advanced Analytics: High proficiency in Microsoft Excel / Google Sheets (advanced formulas, PivotTables, Power Query, VBA/AppsScript, or data connections) for ad-hoc financial and operational analysis.
• Business Acumen & Domain Literacy: Ability to define, track, and interpret core business KPIs across operational domains (e.g., procurement spend, inventory turnover, customer acquisition costs, churn rates, accounts receivable aging).
• Statistical Analysis & Data Validation: Capability to perform variance analysis, trend forecasting, and data reconciliation between source systems (ERPs, CRMs) and reporting platforms.
• Technical Scripting (Bonus): Basic-to-intermediate scripting capabilities in Python or R (using libraries like pandas, numpy, or matplotlib) for automated data cleaning and statistical modeling.
• Stakeholder Management & Storytelling: Clear written and verbal communication skills to explain technical data models, present insights to cross-functional leads, and draft executive summaries.
• Professional Attributes: High analytical curiosity, rigorous attention to data accuracy, structured problem-solving skills, and the ability to meet tight reporting deadlines during period-end cycles.