Overview
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. 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.
Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees, we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.
Starting January 26, 2026, Microsoft AI (MAI) employees who live within a 50- mile commute of a designated Microsoft office in the U.S. or 25-mile commute of a non-U.S., country-specific location are expected to work from the office at least four days per week. This expectation is subject to local law and may vary by jurisdiction.
Responsibilities
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.
Over time, you’ll have opportunities to take on broader ownership and deepen your expertise, supported by coaching and mentoring and working alongside other talented engineers in the team.
Qualifications
Required Qualifications:
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.
Preferred Qualifications:
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.
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This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.
Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about **requesting accommodations.**