Senior Data establish robust 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 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. Build automated reporting and insight-generation capabilities that reduce manual analysis and improve decision speed. Must-have 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, 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. Practical experience using AI or automation to improve data engineering, reporting, documentation, testing, monitoring, migration or developer productivity. Strong-to-have experience Payments, settlement, reconciliation, fees, chargebacks, merchant reporting or finance-domain data. CRM-side data flows and reverse-ETL patterns, especially HubSpot, Salesforce, Zendesk or similar platforms. M can say “no” or “not yet” with evidence. Is hands-on enough to debug pipelines and models, while senior enough to set standards and mentor others. Has used AI or automation in a real data-engineering context to speed up delivery, not just as a novelty, and can describe the guardrails they put around it. #J-18808-Ljbffr
Senior Data & AI Platform Engineer employer: OrderYOYO
At OrderYOYO, we pride ourselves on being an exceptional employer, offering a vibrant and supportive work culture that prioritises personal development and employee success. As an Employee Enablement Manager, you'll have the unique opportunity to shape training initiatives across a high-growth environment, collaborate with diverse teams, and make a tangible impact on our workforce. With tailored growth plans and a commitment to fostering a team-first atmosphere, your contributions will be valued and recognised as we collectively drive towards our ambitious goals.
