Description :
Key Responsibilities :
Database & Data Pipeline Management :
- Build, maintain, and optimize data pipelines to integrate data from multiple sources (internal systems, external APIs, flat files, etc.
- Ensure data quality, integrity, and accuracy across databases.
Analytics & Insights :
Perform exploratory and diagnostic data analysis to identify patterns and trends.Support business decision-making with data-driven insights across sales, operations, buying, planning, and finance.Automate recurring analytical workflows and reports.Dashboard & Reporting Development :
Design and maintain interactive dashboards and reports (using Power BI, Tableau, or equivalent).Create role-specific dashboards tailored to Planning, Sales, Buying, Ops, and Finance teams.Track KPIs, performance metrics, and operational efficiency indicators.Cross-Functional Collaboration :
Work with business teams to understand requirements and translate them into analytical solutions.Present insights clearly through visualizations and reports.Document data sources, methodologies, and assumptions for stakeholders.Skills & Qualifications :
Education :
Bachelors degree in Statistics, Mathematics, Economics, Computer Science, Engineering, or related field.Technical Skills :
Strong SQL skills for data extraction and database management.Hands-on experience with data pipeline tools (ETL, Airflow, dbt, or similar).Proficiency in Excel / Google Sheets for quick analysis.Experience with BI / dashboard tools (Power BI, Tableau, Looker, or similar).Exposure to Python / R for data analysis and automation (preferred).Understanding of relational databases and data warehousing concepts.Experience with cloud databases (Snowflake, BigQuery, Redshift, Azure).Soft Skills :
Strong analytical and problem-solving mindset.Clear communication and ability to explain insights to non-technical stakeholders.Detail-oriented with strong organizational skills.Collaborative and proactive in a fast-paced environment.Nice-to-Have :
Knowledge of version control tools (Git).Familiarity with A / B testing or experimentation.Prior exposure to financial or operational analytics(ref : hirist.tech)