Senior Data Analyst
Data Analysis
Salary
Location
Job Overview And Responsibility
- Operational Reporting & Dashboarding: Design, build, and maintain real-time dashboards and dynamic reporting systems (using tools such as Looker, BigQuery, Google Data Studio, etc.) to monitor day-to-day operational performance across all services. - Performance Diagnosis & Opportunity Sizing: Work alongside OE to proactively analyze key metrics, identify performance gaps or operational bottlenecks, and quantify the business impact of inefficiencies. - Insight-Driven Project Support: Provide deep-dive analyses and actionable insights to back strategic initiatives led by OE — supporting decisions related to process redesign, automation rollouts, or partner engagement programs. - Data Automation & System Enhancement: Collaborate with BI teams to automate data pipelines, develop data models for operational workflows, and ensure high data integrity across systems. - Data Governance & Best Practices: Define and uphold standards for data governance, quality assurance, and KPI definitions to ensure consistent measurement across the organization. - Predictive Analytics & Experimentation: Use models and testing methods (e.g., A/B testing, segmentation) to evaluate retention programs, ops pilots, and product changes from an operational perspective.
Required Skills and Experience
1. Experience - 3-5 years of experience in operations data analytics, business intelligence, or a related role, preferably within a technology, e-logistics, or e-commerce company. - Hands-on experience working directly with operational leaders or OE teams to drive measurable business improvements. - Candidates with experience in ops-related BA roles (e.g., Lazada or Shopee transformation projects) are preferred but not required. Attitude - Highly proactive and solution-oriented, with a strong bias for turning data into action. - Comfortable in high-velocity, ambiguous environments; able to prioritize and adapt quickly based on business needs. - Collaborative mindset, with a natural ability to partner with cross-functional teams (Operations, Product, CRM, Tech). 2. Skills - Advanced Analytics: Proficient in SQL (BigQuery preferred), Excel, and Looker or equivalent BI tools; capable of writing complex queries, building multi-layer dashboards, and generating self-service analytics. - Data Modeling & Automation: Strong understanding of relational databases, ETL processes, and building scalable data workflows. - Operational Insight Extraction: Ability to translate operational data into meaningful performance narratives, identify systemic gaps, and support OE-led interventions. - Problem Solving: Structured thinker with strong root-cause analysis skills and a results-oriented approach to performance optimization. 3. Knowledge - Solid understanding of operational workflows, fulfillment models, and key drivers of efficiency and service quality in multi-service environments. - Familiarity with Agile methodologies, experimentation (A/B testing), and data-driven product iteration processes is a plus. - Bachelor's degree in data science, business analytics, computer science, or related disciplines.
Why Candidate should apply this position
- Benefits will be shared in details for successful candidates.
Preferred skills and experiences
- Prioritize candidates who can onboard as soon as possible
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