Responsibilities
- Collect, analyze, and interpret data from multiple internal and external sources to support business decision-making.
- Design, develop, and maintain interactive dashboards and reports using BI tools such as Power BI, Qlik Sense, or Tableau.
- Collaborate with business stakeholders to define data requirements, KPIs, and performance metrics aligned with organizational goals.
- Transform raw data into meaningful insights through statistical analysis, visualization, and storytelling techniques.
- Ensure data accuracy and consistency by validating datasets, identifying anomalies, and coordinating with data engineering teams to resolve issues.
- Perform trend and variance analysis to identify opportunities, risks, and performance improvement areas.
- Develop and document data models and calculations that support standardized business reporting and self‑service analytics.
- Support data‑driven initiatives by providing ad hoc analyses and actionable recommendations to business teams.
- Automate recurring reports and analytical workflows to improve efficiency and reduce manual work.
- Monitor data refresh schedules and BI system performance, ensuring timely delivery and high availability of insights.
- Bachelor’s degree in Information Technology, Information Systems, or a related field; Master’s degree is a plus.
- Minimum 3 years of professional experience as a Data Analyst, BI Analyst, or Reporting Specialist.
- Hands‑on experience developing interactive dashboards and analytical reports using Power BI, Qlik Sense, or Tableau.
- Strong proficiency in SQL for data extraction, joining, and transformation from multiple sources.
- Understanding of data modeling concepts (star schema, snowflake schema) and KPI/metric definition for reporting purposes.
- Experience collaborating with business stakeholders to define and document analytical requirements.
- Familiarity with data warehouses or cloud data platforms (e.g., Snowflake, BigQuery, Redshift, Azure Synapse).
- Proficient in English and Indonesian Language.
- Proficient in Power BI, Qlik Sense, or Tableau for creating dashboards, visual analytics, and storytelling with data.
- Strong command of SQL (joins, subqueries, window functions, CTEs) for extracting and transforming data from multiple sources.
- Experience with ETL/ELT concepts and collaboration with data engineers for data preparation.
- Understanding of dimensional modeling (star/snowflake schemas), data marts, and KPI definitions to support self‑service analytics.
- Working knowledge of Excel (advanced functions, Power Query, pivot tables) and experience with Python (pandas, numpy) or R for statistical analysis or automation.
- Familiarity with cloud environments such as Snowflake, BigQuery, Amazon Redshift, or Azure Synapse Analytics.
- Analytical Mindset: Strong ability to interpret data, identify trends, and translate findings into actionable recommendations.
- Business Understanding: Able to connect data insights with business processes and strategic goals.
- Communication Skills: Clear and confident in presenting analytical results to stakeholders of varying technical backgrounds.
- Attention to Detail: Ensures data accuracy and consistency when preparing reports or dashboards.
- Critical Thinking: Evaluates data quality, questions assumptions, and validates findings before presentation.
- Collaboration: Works effectively with data engineers, IT, and business teams to define metrics and requirements.
- Adaptability: Comfortable working in dynamic environments with evolving data sources and business priorities.
- Storytelling with Data: Skilled in transforming complex datasets into intuitive and meaningful visual narratives.