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You’ll sit inside Microsoft’s most advanced AI and search organization, a collective of creators, engineers, and product teams building the next generation of human-centered AI. The Microsoft AI org is built on quality, simplicity, and trust and consists of global products like Copilot, Bing, Edge, Clarity, SwiftKey and MSN. You’ll join the SwiftKey team that powers how hundreds of millions of people communicate every day - directly shaping the cloud services, telemetry pipelines, data processing systems, and reliability foundations that serve them worldwide. We build secure, compliant, resilient, and observable services that enable AI-powered mobile experiences. As a Data Engineer, you will build and operate high‑quality data ingestion, transformation, and validation pipelines that power experimentation, insights, and AI features across SwiftKey. This opportunity allows you to grow deep service engineering skills, develop hands‑on expertise with large‑scale data systems, and contribute to Microsoft’s mission of delivering trusted, intelligent experiences.
Job Responsibility:
Build and operate production services that ingest, validate, transform, and serve data in cloud-hosted environments (we use containerized and serverless services in Azure)
Design, maintain, and improve data and model infrastructure used to process, store, distribute, and access large datasets, ensuring availability and correctness (we use modern data lake storage and platforms such as Databricks, Azure Synapse, and Spark)
Monitor the health and performance of live data services using telemetry and alerts, investigate service issues, and participate in incident response [and on-call rotations] to reduce disruption for users and downstream systems
Partner with other engineers, product managers, and applied scientists to deliver high-quality data and production-ready services that support analytics, experimentation, and AI feature development
Apply security, privacy, and compliance standards across pipelines and services, managing data access and ensuring adherence to applicable policies and regulations
Requirements:
Bachelor's Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field AND experience in business analytics, data science, software development, data modeling or data engineering work
OR Master's Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field AND experience in business analytics, data science, software development, data modeling or data engineering work
OR equivalent experience
Experience writing code in Python and SQL, or other relevant data-focused programming languages
Experience building or operating production data pipelines using distributed data processing platforms, such as Apache Spark–based systems (e.g., Databricks or Azure Synapse)
Experience working with large-scale data storage and table formats commonly used in data lake architectures
Familiarity with cloud platforms (Azure preferred) and service engineering practices, including building, deploying, and operating containerized workloads using modern orchestration platforms, monitoring system health, and supporting the ongoing reliability of distributed cloud services
Nice to have:
Experience working with event-driven or streaming data ingestion systems (for example Azure Event Hubs, Kafka or similar technologies)
Experience working with large-scale consumer data in production services
Experience applying data governance, data compliance, and data security practices in production data systems