Senior Data & AI Platform Engineer
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Job Description
Senior Data & AI Platform Engineer modernizing OrderYOYO’s data platform for online ordering solutions serving independent restaurants. Leading Microsoft Fabric, Power BI, pipelines, migrations and AI-enabled analytics.
Responsibilities:
- Own the continuity, evolution and AI-enablement of OrderYOYO’s modern data platform during a critical scaling phase
- 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 orchestration, monitoring, alerting, data-quality checks and incident response
- Use AI and automation to accelerate ETL/ELT development, data mapping, documentation, testing, report generation, monitoring and data-quality management
- Design 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
- Set data-engineering standards covering 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
- Build automated reporting and insight-generation capabilities that reduce manual analysis and improve decision speed
- Provide senior technical leadership for data engineering delivery
Requirements:
- 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
- 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, including 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
- Practical experience using AI or automation to improve data engineering, reporting, documentation, testing, monitoring, migration or developer productivity
- Strong-to-have experience with payments, settlement, reconciliation, fees, chargebacks, merchant reporting or finance-domain data
- Strong-to-have CRM-side data flows and reverse-ETL patterns, especially HubSpot, Salesforce, Zendesk or similar platforms
- Strong-to-have M&A or acquired-company data integrations
- Strong-to-have NoSQL-to-analytics modelling
- Strong-to-have GA4, BigQuery export, Google Ads / SEM feeds, Segment or other event and marketing analytics sources
- Strong-to-have Azure OpenAI, LLMs, RAG, AI agents, prompt/version management or AI-assisted development workflows
- Strong-to-have AI-generated reporting, natural-language analytics, business copilots, automated insight generation or merchant/customer intelligence tools
- Strong-to-have responsible AI and governance experience, including RBAC, PII handling, audit logs, human approval flows, explainability and GDPR-conscious design
Benefits:
- Fully remote work arrangement
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