Data & AI platform engineer

OrderYOYO; United States; Remote; USD 65,000 - 108,000; Full time

Benefits offered by this job

Remote work

Job summary

OrderYOYO приглашает специалиста по данным для построения конвейеров и lakehouse, поддерживающих управленческую отчетность и инсайты для мерчантов на нашей платформе. Вы будете отвечать за дизайн, реализацию и эксплуатацию в продакшн, сотрудничая с лидерами, финансами и продуктом.

Требуется глубокий опыт работы с Fabric/Synapse/Databricks, SQL, Python/PySpark и построением версионируемой платформы данных с фокусом на надежность и масштабируемость.

Qualifications

• Опыт проектирования и эксплуатации production‑grade data решений на платформе современного уровня.
• Глубокие знания SQL и T‑SQL, оптимизация запросов и моделей данных.
• Навыки работы с производственными пайплайнами данных и мониторингом качества данных.

Responsibilities

• Спроектировать и построить конвейеры данных и lakehouse в Fabric.
• Разрабатывать и запускать продакшн‑пайплайны на Python/PySpark.
• Обеспечивать мониторинг, качество данных и управляемые метрики.

Skills

SQL

Python

PySpark

Azure Fabric

Data modeling

Tools

Fabric / Synapse / Databricks

Power BI

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. You’ll own complex changes from technical design through release and production operation, working closely with the leadership team, Finance, Product and fellow engineers. Your work will improve the accuracy and reliability of our reporting, merchant insights and finance data, while reducing routine manual Finance work.

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.