Data & AI platform engineer for restaurants

OrderYOYO; United States; Remote; USD 110,000 - 140,000; Full time

Benefits offered by this job

Remote role

Quarterly in-person gatherings

Job summary

OrderYOYO is seeking a senior data platform engineer to design, build, and operate production-grade data solutions in Microsoft Fabric. You will run end-to-end data pipelines, manage lakehouse and platform cost, and lead migrations from legacy systems while ensuring governance and reliability.

You will work with executives and cross-functional teams to deliver AI-powered data products and insights, including RAG and Azure OpenAI integrations, across the business.

Qualifications

• 6+ years of relevant data experience and production-level data engineering responsibilities.
• Hands-on expertise with Microsoft Fabric, Synapse, Databricks or Delta in production environments.
• Strong SQL/T-SQL skills including complex modelling and tuning.
• Proficient in Python or PySpark for production data pipelines.
• Experience with lakehouse architectures, partitioning, and performance considerations.
• Knowledge of Azure components (ADLS/OneLake, RBAC, Key Vault) and governance concepts.

Responsibilities

• Design, build and operate production-grade data solutions in Microsoft Fabric.
• Build and run production pipelines in Fabric, Python and PySpark with testable code.
• Design scalable ingestion and transformation patterns and manage cost and capacity.
• Lead migrations from legacy to modern platforms with proper governance and decommissioning.
• Operate the platform in production: monitoring, incidents, data quality checks and lineage.
• Incorporate AI features (RAG, Azure OpenAI) and deliver AI-driven data products.

Skills

Microsoft Fabric

SQL/T-SQL

Python

PySpark

Data modeling

Azure data services

Delta Lake

Performance tuning

Cost optimization

AI engineering

Tools

Terraform

Bicep

Job description

Описание:

Join OrderYOYO’s Data team to build the data pipelines and lakehouse that power executive reporting and merchant insights across our platform, and automate how we deliver finance data and AI-driven data products to the rest of the business.

Задачи:

Design, build and operate production-grade data solutions in Microsoft Fabric across Lakehouse, Warehouse, notebooks, pipelines and related platform capabilities. Build and run production pipelines in Fabric, Python and PySpark that are tested and maintainable, not just notebooks. Design ingestion and transformation patterns that scale across multiple source systems, databases and business domains while controlling source impact, concurrency and platform cost. Manage Fabric capacity and cost, and retire redundant legacy layers. Lead migrations from legacy to modern platforms with metric parity, stakeholder sign-off, change control and safe decommissioning. Run the platform in production: monitoring, alerting, incident triage, root-cause analysis, data-quality checks, lineage and runbooks. Diagnose and resolve production issues across SQL, Spark, pipelines and semantic models, including performance degradation, data failures and capacity/resource constraints. Support and evolve governed semantic models and reusable metric definitions, working closely with analytics and business stakeholders to ensure performance, consistency and reliability. Build AI into the platform and our delivery: RAG, Azure OpenAI and agents, with prompt and version management. Deliver applied data science such as churn, recommendations, personalisation, fraud or risk models, and show the results. Work with executives, Finance, Product and engineering, and judge when to move fast, standardise, automate or hold.

Требования:

6+ years of relevant data experience, including substantial recent hands-on data engineering or data-platform engineering responsibility in production environments. Demonstrated ability to independently take a data-engineering problem from requirements and technical design through implementation, production deployment, monitoring and ongoing operation. Deep hands-on Microsoft Fabric, or strong Synapse, Databricks or Delta experience with a clear path to Fabric. Strong understanding of lakehouse architecture and Delta-based data engineering, including partitioning, schema evolution, file optimisation and performance considerations. Expert SQL and T-SQL, including complex modelling and tuning. Production-grade Python or PySpark. Strong experience designing and implementing incremental data ingestion patterns, including approaches such as CDC, change tracking or watermarks, with reliable merge/upsert, replay and idempotent processing. Experience with analytical and semantic data modelling, ideally with Power BI/Fabric semantic models, including performance optimisation, governance and reusable business metrics. Working knowledge of Azure platform fundamentals including Azure SQL, ADLS/OneLake, Entra ID, managed identities, RBAC and Key Vault. A track record of leading a legacy-to-modern migration. Real, hands-on AI engineering beyond out-of-the-box Copilot. Concrete data science or ML models you delivered, with results. Будет плюсом: Strong Power BI/Fabric experience, including Direct Lake, DAX, semantic model performance tuning, incremental refresh and capacity considerations; Infrastructure-as-Code experience with Terraform, Bicep or equivalent tooling; Data platform experience in SaaS, marketplace, fintech, payments, e-commerce or multi-region businesses

Условия:

A salary of up to £80,000 per year (or local equivalent). A remote role, with quarterly in-person gatherings at one of our global offices. Ownership of a business-critical data and AI platform. A collaborative, international engineering team.