Business Analytics professional

Job Purpose



The Data Analyst is responsible for collecting, cleaning, analyzing, and transforming data from various company systems (ERP, CRM, Production, Procurement, etc.).

He ensures that data is accurate, consistent, and accessible, and develops interactive dashboards and reports that track each department’s KPIs (Sales, Procurement, Production).

The role works closely with the IT department to automate data flows and reporting processes, supporting effective data-driven decision-making.



Key Responsibilities



Gather and organize data from multiple systems and sources.



Clean, validate, and maintain data integrity to ensure reliable reporting.



Conduct data analysis to identify trends, patterns, and performance insights.



Define and measure department KPIs in coordination with relevant stakeholders.



Build automated and interactive dashboards using Power BI, Tableau, or similar tools.



Collaborate with the IT team to integrate and automate data pipelines and system connections (APIs, databases, ERP).



Deliver regular performance reports and analytics summaries to management.



Support departments with data interpretation and KPI monitoring.



Ensure data security and compliance with company policies.



Continuously seek opportunities to improve data quality, reporting efficiency, and analytical capabilities.



Qualifications & Requirements



Education:



Bachelor’s degree in Data Analytics, Computer Science, Statistics, Information Systems, or related field.



Experience:



Minimum 2–4 years of experience as a Data Analyst or Business Intelligence Analyst.



Hands-on experience working with ERP/CRM data or in cross-functional business environments (Sales, Procurement, Production).



Technical Skills:



Strong knowledge of SQL and relational databases.



Proficiency in Power BI, Tableau, or similar visualization tools.



Advanced skills in Excel (PivotTables, Power Query, formulas).



Understanding of ETL processes and data cleaning techniques.



Knowledge of scripting languages such as Python or R (a plus).



Soft Skills:



Excellent analytical and problem-solving abilities.



Strong attention to detail and data accuracy.



Clear communication skills to explain data insights to non-technical audiences.



Collaborative mindset to work with IT and business teams.



Time management and organization skills.