
51 - 200 employees
Founded 2015
🍽️ Food & Beverage
📣 Marketing
📦 Logistics
đź’° $6M Post-IPO Equity - OrderYoyo on 2022-03
Food & Beverage • Marketing • Logistics
OrderYOYO is an online ordering and marketing platform for restaurants and takeaways that provides bespoke websites and mobile apps, a cloud POS, integrated payment processing (YOYOPay), and targeted marketing services (email, SMS, app push, Google Ads, social media). It offers features like loyalty programs, reservations, analytics via a My Business app, and dedicated support to help restaurants capture direct orders, reduce commission fees, and grow customer retention. The company positions itself as a Google Partner and serves thousands of restaurants with tailored digital storefronts and marketing campaigns.
đź•’ May 13
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51 - 200 employees
Founded 2015
🍽️ Food & Beverage
📣 Marketing
📦 Logistics
đź’° $6M Post-IPO Equity - OrderYoyo on 2022-03
Food & Beverage • Marketing • Logistics
OrderYOYO is an online ordering and marketing platform for restaurants and takeaways that provides bespoke websites and mobile apps, a cloud POS, integrated payment processing (YOYOPay), and targeted marketing services (email, SMS, app push, Google Ads, social media). It offers features like loyalty programs, reservations, analytics via a My Business app, and dedicated support to help restaurants capture direct orders, reduce commission fees, and grow customer retention. The company positions itself as a Google Partner and serves thousands of restaurants with tailored digital storefronts and marketing campaigns.
• Own the continuity and evolution of OrderYOYO’s modern data platform during a critical scaling phase. • Lead the migration from legacy reporting and metric tooling into a governed Microsoft Fabric platform. • Keep business-critical BI and semantic models reliable. • Improve data pipeline stability and monitoring. • Support CRM data integration. • Provide senior technical leadership for data engineering delivery. • Lead hands-on Microsoft Fabric architecture across lakehouse, warehouse, notebooks, semantic models, Git-backed delivery and production governance. • Drive migration from legacy reporting and metric tooling into a governed Fabric semantic layer, including parity testing, stakeholder sign-off and safe decommissioning. • Own and improve data pipelines across APIs, files, events and operational stores; establish robust orchestration, monitoring, alerting, data-quality checks and incident response. • Design high-quality Power BI semantic models, DAX measures and reusable metric definitions for leadership, finance, commercial, product, marketing, payments and support reporting. • Support CRM and operational data integrations, including outbound data feeds, identity mapping, schema mapping, reverse-ETL patterns and monitoring. • Create reliable ingestion and modelling patterns for acquired businesses, so future integrations are repeatable, auditable and faster to execute. • Set data-engineering standards: definition of ready/done, code review, release discipline, documentation, runbooks and platform change governance. • Mentor engineers and analysts and translate business-critical data needs into pragmatic technical delivery.
• 6+ years in modern data warehousing, analytics engineering or data platform engineering, ideally in a SaaS, marketplace, fintech, payments, e-commerce or multi-region B2B2C environment. • Strong Microsoft Fabric capability, or deep Azure Synapse / Databricks experience with clear ability to specialise quickly in Fabric. • Expert SQL/T-SQL plus strong Python or PySpark, with a track record of building maintainable ELT/ETL pipelines and analytical data models. • Strong Power BI and DAX experience, including semantic modelling, incremental refresh, performance tuning, model governance and capacity/cost awareness. • Experience leading legacy-to-modern data platform migrations, including metric parity, stakeholder validation, change control and safe decommissioning. • Experience operating production data systems: monitoring, alert design, incident triage, root-cause analysis, data-quality checks, lineage and runbooks. • Comfortable with Git-based data engineering workflows, pull requests, release discipline and standards for notebooks, pipelines and semantic model changes.
• Competitive salary • Growing international company • Growth opportunities
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