Note: The job is a remote job and is open to candidates in USA. Ora Apps Inc. is an online clothing brand seeking a Lead Analytics/Data Engineer. This role focuses on owning and governing their Looker semantic layer, requiring expertise in Looker and LookML, as well as a background in retail or ecommerce.
Responsibilities
- Establish and enforce naming, ownership, and documentation standards for Snowflake schemas and objects — including flagging tables with no downstream Looker reference or owned by generic/departed-employee service accounts
- Build and maintain reconciliation logic between systems (e.g., Shopify ↔ NetSuite ↔ Avalara tax reconciliation, order status/fulfillment lifecycle across Shopify → NetSuite → Twin Oaks)
- Design, build, and refactor LookML models, explores, views, and derived tables that map cleanly to underlying Snowflake objects — not 1:1 dashboard-driven sprawl
Skills
- Must have retail/ecommerce recent background – this company is a online clothing brand – needs similar background industry experience
- This role centers on owning and governing our Looker semantic layer specifically – deep looker and LookML expertise
- Needs smaller / startup company recent experience. Someone who has only worked for huge companies will NOT work
- Ownership of a single retail/ecommerce company's Looker + Snowflake + Shopify/NetSuite/daasity/toolio/fivetran stack
- 7+ years in BI/analytics engineering with production Looker/LookML experience (models, explores, derived tables, PDTs, access filters) — not just dashboard consumption
- 4+ years of advanced SQL in Snowflake or a comparable cloud warehouse (window functions, incremental merge patterns, query performance tuning)
- Direct experience with retail/ecommerce data models: order lifecycle, fulfillment, inventory, returns, customer/CDP data — ideally spanning a DTC platform (Shopify/BigCommerce/Salesforce Commerce) plus an ERP (NetSuite, Microsoft Dynamics, SAP)
- Experience working within a vendor-managed or templated ELT/transformation framework (Daasity, Fivetran + dbt, Matillion, or similar) — comfortable extending vendor patterns without introducing untracked one-offs
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