Loại hình
Toàn thời gian
Hình thức
Tại văn phòng
Cấp bậc
Nhân viên
Ngành nghề
CNTT - Phần mềm
Mức lương
Thương lượng
Địa điểm
Hồ Chí Minh, Hồ Chí Minh, Hồ Chí Minh
Tổng quan
- Advanced Dashboarding & Insight Delivery
- Lead the design, development, and optimization of scalable dashboards that provide clear, actionable insights for business stakeholders
- Standardize metric definitions and ensure consistency across all reporting layers (dashboards, datamart, and ad-hoc analysis)
- Drive adoption of dashboards by aligning with business use cases and continuously improving usability and relevance
- Proactively monitor dashboard performance and usage; optimize, consolidate, or decommission low-value reports to maintain an efficient reporting ecosystem
- Introduce best practices in data visualization, storytelling, and KPI tracking to enhance decision-making
- Advanced Data Analysis & Business Impact
- Perform deep-dive analysis on large, complex datasets to uncover trends, behavioral patterns, and business opportunities across the customer lifecycle
- Translate business problems into analytical frameworks and deliver data-driven recommendations to improve acquisition, engagement, and profitability
- Act as a key analytics partner for Business Units (BUs), leading high-impact ad-hoc analyses and strategic investigations
- Apply advanced analytical techniques (e.g., cohort analysis, funnel analysis, segmentation) to support business strategy
- Data Governance & Documentation
- Own and maintain a centralized KPI dictionary and data definitions to ensure alignment across teams
- Ensure all metrics, business logic, and data transformations are well-documented, version-controlled, and accessible to both technical and non-technical stakeholders
- Promote data transparency and standardization across reporting and analytics workflows
- Data Quality & Pipeline Optimization
- Collaborate closely with Data Engineering and related teams to ensure data pipelines are reliable, scalable, and optimized for analytics use cases
- Define and monitor data quality frameworks, including validation rules, anomaly detection, and reconciliation processes
- Proactively identify data gaps, inconsistencies, and inefficiencies, and drive resolution to maintain high data integrity
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