Sales Analytics Executive

Job description

Kredivo is looking for an experienced Data Analyst to support analytics needs for the Business Development function. This role is responsible for tracking and analysis for key metrics and KPIs for the sales promotors, sales operation, merchant acquisition, and business development departments. The successful candidate will be working closely with various stakeholders, namely product manager, product analyst, data engineer, and data scientist to deliver actionable insights and ensure data-driven decision-making. Responsibilities: Monitoring and tracking key business metrics and KPIs such as GMV growth, promo spend efficiency, sales channel performance, merchant acquisitions, and store performances. Creating monthly sales team targets, incentive plans, and performance tracking. Collecting and organizing data from various sources and generating reports and dashboards. Analyzing sales promoter performance, patterns, and metrics and presenting insights to stakeholders. Collaborating with the sales promoter team to understand operational needs and deliver data-driven solutions. Identifying opportunities for sales promoter growth and improvement. Providing support for internal product development from data perspective. Developing, maintaining, and owning sales-related data marts. Documenting data assets including data marts, automated pipelines, insights, and root cause analysis. Requirements: Bachelor’s Degree preferably in quantitative subject (e.g. Computer Science, Engineering, Economics, or Mathematics) Minimum 4 years’ experience as Business Data Analyst, Sales Data Analyst, or Product Analyst. Excellent analytical skills. You need to be comfortable with data – analyze it, question its validity, interpret it, and develop recommendations based on it. Advanced SQL skills are mandatory. Proficiency in Microsoft Excel or Google Sheets is required. Great communication skills to translate complex data into clear business insights for non-technical stakeholders. Experience with data visualization tools, e.g. Tableau, PowerBI, Mode, or Looker. Proficient in English, with the ability to converse professionally in both written and verbal communication. Experience with data warehouse modelling is a strong advantage. Experience with data pipeline automation (Airflow, dbt) and programming skills in Python are a strong advantage. Comfortable working in a dynamic and fast-paced environment. #LI-AS1