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Business Intelligence Manager (Ecommerce)

AIRR LABS · Hồ Chí Minh
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Loại hình
Toàn thời gian
Hình thức
Tại văn phòng
Cấp bậc
Trưởng / Phó phòng
Ngành nghề
Ngành nghề khác
Mức lương
Thương lượng
Địa điểm
Hồ Chí Minh, Hồ Chí Minh, Hồ Chí Minh

Tổng quan

  • Metric governance: A single source of truth for marketplace and social commerce KPIs, and data contracts for all published datasets.
  • Business ontology: The shared model of core business entities (clients, brands, shops, SKUs, orders, campaigns, KOLs and live sessions), their relationships and hierarchies, with master data giving each entity one ID across platforms.
  • Certified data models: Business-ready datasets that underpin all dashboards, applications and client reporting.
  • Reporting and insights: Dashboards and reporting for internal teams, and client-facing reporting in AIRR Space.
  • Data quality: Validation prior to publication, and daily reconciliation of orders and GMV against marketplace Seller Centre data.
  • Metric Governance and Business Ontology
  • KPI framework: Establish and govern a single source of truth for marketplace and social commerce KPIs (e.g. GMV, net orders, cancellations and returns, live-session GMV, ROAS), with documented definitions and named business owners. Resolve conflicting definitions across teams.
  • Business ontology: Define and own the business ontology for marketplace and social commerce: core entities (client, brand, shop, SKU, order, campaign, KOL, live session), their relationships and hierarchies (e.g. client → brand → shop → SKU), and the business rules that govern them. Maintain master data so each entity has one ID across platforms, for example mapping Lazada, Shopee and TikTok Shop…
  • Data contracts: Define and maintain data contracts for all published datasets, covering grain, schema, business meaning, ownership and freshness requirements.
  • Certification: Certify trusted datasets for business use and deprecate obsolete or duplicate reports.
  • Business context for AI: Package the business ontology, glossary, metric definitions and query rules for the company’s AI data assistant, so that its answers match certified dashboards.
  • Data Modelling and Reporting
  • Data modelling: Design and build analytics-ready data models in SQL, migrating legacy stored procedures and report-level logic into tested, documented models.
  • Dashboards and reporting: Lead the development of dashboards and reports for senior management, marketplace operations, live commerce, KOL and client teams across Southeast Asia, delivering clear and actionable insights.
  • Brand reporting: Partner with Product and Engineering to define the data and reporting delivered to clients and brands.
  • Data Quality and Reconciliation
  • Quality controls: Implement automated data quality checks prior to publication. Ensure every production issue is resolved through root-cause analysis and a preventive control.
  • Reconciliation: Own the daily reconciliation of orders and GMV against Lazada, Shopee and TikTok Shop Seller Centre data, and manage exceptions through to resolution with clear ownership and timelines.
  • Peer review and migration: Participate in peer review of all changes to data models, and lead parallel-run validation when reporting migrates from legacy sources to the new platform.
  • Stakeholder Management
  • Validation and change control: Run validation sessions with business owners before a metric goes live, explaining calculation choices in plain language and securing sign-off. Manage metric change requests so that definitions change only with the owner’s approval and all affected reports are updated together.
  • Product and Engineering partnership: Act as the BI counterpart to the Heads of Product and Engineering. Ensure new features and internal applications define their data requirements before build, and assess the reporting impact of upstream changes before they reach dashboards or client reports.
  • Adoption of certified data: Turn ad-hoc requests into reusable, certified datasets rather than one-off reports. Move teams off legacy reports and spreadsheets onto certified data, with owner sign-off on matched numbers before each switch.
  • Executive communication: Present commercial performance to senior leadership using certified metrics only, explaining the key drivers and recommending actions.
  • Standards and Best Practice
  • BI standards: Establish and maintain standards for data modelling, naming, testing, documentation and visualization.
  • Continuous improvement: Raise the quality of the data team's work through code review and knowledge sharing. Keep abreast of developments in analytics tools and practices, and identify opportunities to apply them.

Quyền lợi

  • BIC health insurance and periodic health check-ups
  • 12 days of paid annual leave, plus additional company recharge days
  • New laptop, monitor and other work equipment provided as required by the role
  • Annual company trip
  • Training and development programs, both in Vietnam an overseas, tailored to different levels and departments
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