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Work collaboratively with other product engineers, Product Managers, and platform engineers to take ambiguous projects and mold them into amazing experiences. Ship high-quality, well-tested, secure, and maintainable code. Find a path to get things done despite roadblocks to get your work into the hands of users quickly and iteratively. Enjoy working in a fast-paced, design-driven, product development cycle. Embody our Culture and Values. Bachelor's degree in computer science, or related technical discipline AND 4+ years technical engineering experience building mobile app backend applications with coding in languages including, but not limited to, C#, Python, C++, Rust, Java, Golang, Ruby OR equivalent experience. 4+ years' experience building backend API for mobile apps such as GraphQL/Rest APIs/Protobuf/Thrift, and streaming protocols such as websocket/SSE/WebRTC with familiarity in backend and mobile data schema code generation or consistency, version control for mobile releases, analytics, feature flags, a/b testing framework. 4+ years' experience building scalable services on top of public cloud infrastructure like Azure, AWS, or GCP. Extensive use datastores like RDBMS, key-value stores, etc. 4+ years' experience building distributed systems at scale and extensive systems knowledge that spans bare-metal hosts to containers to networking. Experience working with AI platforms, frameworks, and APIs. Ability to identify, analyze, and resolve complex technical issues, ensuring optimal performance, scalability, and user experience. Dedication to writing clean, maintainable, and well-documented code with a focus on application quality, performance, and security. Demonstrated interpersonal skills and ability to work closely with cross-functional teams, including product managers, designers, and other engineers. Ability to clearly communicate complex technical concepts to both technical and non-technical stakeholders. Passion for learning new technologies and staying up to date with industry trends, best practices, and emerging technologies in web development and AI. Ability to work in a fast-paced environment, manage multiple priorities, and adapt to changing requirements and deadlines. 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Embody our Culture and Values. Bachelor's Degree in Computer Science, or related technical discipline AND 6+ years technical engineering experience with web technologies including, but not limited to, Typescript and React 3+ years people management experience. Bachelor's Degree in Computer Science, or related technical discipline AND 8+ years technical engineering experience with coding in languages including, but not limited to, Typescript and React OR equivalent experience. 6+ years people management experience. Take a user-centric approach to product development, prioritizing solutions that result in the best user experience and have the technical expertise to pull it off. Thrive in a fast-paced, collaborative environment and are comfortable making progress in ambiguity. Enjoy working closely with cross-functional partners and teammates in an inclusive, curious culture. Have strong opinions about best investments to make in establishing the most delightful and performant web engineering system.", "stars": 0.0, "medallionProgram": null, "location_flexibility": null, "work_location_option": "hybrid", "canonicalPositionUrl": "https://microsoftai.eightfold.ai/careers/job/1970324837018427", "isPrivate": false}, {"id": 1970324837030422, "name": "MTS - Data Engineering ", "location": "Mountain View, California, United States", "locations": ["Mountain View, California, United States", "Redmond, WA, USA"], "hot": 0, "department": "Copilot (P0PS)", "business_unit": "Microsoft AI (QIA5)", "t_update": 1762977277, "t_create": 1755037625, "ats_job_id": 1970324837030422, "display_job_id": 1970324837030422, "type": "ATS", "id_locale": "1970324837030422-en", "job_description": "Data engineers who have built and scaled data systems that others depend on, who take pride in delivering rock-solid data quality, and who genuinely enjoy the craft of data engineering. If you're the type of person who celebrates when your monitoring dashboards show all green and gets energized by the challenge of making data flow seamlessly across complex systems, this role is for you. Join us to architect and implement the data backbone that powers Copilot for millions of users worldwide. You'll own the full data lifecycle - from building lightning-fast ETL pipelines that handle massive scale to crafting experimentation frameworks that drive product decisions. We need someone who thrives on solving complex data challenges, loves collaborating with brilliant teammates, and gets genuinely excited about building infrastructure that just works. In our fast-paced environment, you'll have the freedom to innovate and the support to build world-class data products that make a real impact. By applying to this position, you are required to be local to the San Francisco area or Redmond area and in office 3 days a week. 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. This expectation is subject to local law and may vary by jurisdiction. Master's Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field AND 4+ years experience in business analytics, data science, software development, data modeling, or data engineering OR Bachelor's Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field AND 6+ years experience in business analytics, data science, software development, data modeling, or data engineering OR equivalent experience. Experience building and maintaining production data pipelines at scale using technologies such as Apache Spark, Kafka, or similar distributed processing frameworks. 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Design and maintain high throughput, low latency experimentation reporting pipelines that enable data scientists and product teams to measure model performance and user engagement. Own data quality initiatives including monitoring, alerting, validation, and remediation processes to ensure data integrity across all downstream systems. Implement robust schema management solutions that enable quick and seamless schema evolution without disrupting downstream consumers. Develop and maintain data infrastructure that supports real-time and batch processing requirements for machine learning model training and inference. Collaborate with ML engineers and data scientists to optimize data access patterns and improve pipeline performance for model evaluation workflows. Design scalable data architectures that can handle growing data volumes and evolving business requirements. Implement comprehensive monitoring and observability solutions for data pipelines, including SLA tracking and automated alerting. 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