Overview
The Customer Experience Engineering team is a highly technical, globally operating group responsible for driving customer success on the Azure platform, with a focus on designing and helping customers build production applications and reduce technical debt.
Responsibilities
* Work directly with strategic customer projects worldwide to ensure success on the Azure platform, focusing on production applications and reduction of technical debt.
* Engineer technical artefacts, products, and guidance to optimize customer adoption of Azure.
* Provide positive impact to the strategic direction of Azure engineering by ensuring end-to-end technical details are understood from the customer perspective.
* Develop and mentor technical delivery personnel within the Customer Success organization.
* Travel up to 25% may be required to work on-site with customers across EMEA; occasional in-person work in Redmond, WA may be needed to engage with broader CE&S and Azure engineering teams. CXE Software Engineers are remote workers based across Microsoft locations or home offices, depending on circumstances.
* Engineer distributed applications within architectural scenarios such as Web and IoT.
* Work with programming languages including C#, JavaScript/TypeScript, Java, and Python.
* Design scalable Azure solutions with a focus on performance and resiliency.
* Apply application design patterns and anti-patterns (e.g., MVC, CQRS, SAGA).
* Implement messaging patterns and application integration technologies.
* Interact with and query databases and NoSQL datastores.
* Monitor applications and implement end-to-end telemetry.
* Implement microservice architectures and container-based deployments using Kubernetes, Service Fabric, and related technologies.
* Define CI/CD pipelines to automate testing and release across environments, including blue/green and canary deployments.
* Manage source code using Git or other tools (e.g., TFS).
* Utilize open source technologies and frameworks.
* Model cloud infrastructure based on scale and capacity, providing data-driven recommendations to optimize architecture and performance.
* Apply architectural patterns and anti-patterns for resiliency and geo-availability; leverage cloud networking and hybrid connectivity (e.g., BGP, SD-WAN, ExpressRoute).
* Perform application migrations involving Windows/Linux VMs, databases, NFS/SMB shares, and VDI.
* Manage, monitor, and operate at scale in a cloud environment; implement identity and access control (B2B/B2C) and Azure AD familiarity.
* Define security and governance baselines and use infrastructure-as-code to build, test, and deploy environments.
* Run microservices and container-based workloads in production; engage with CNCF projects and open-source technologies.
* Data and Analytics focus including relational and Open Source databases, Azure Cosmos DB, big data, Databricks, Spark, streaming technologies (Spark streaming, Flink, Kafka streams, Storm), and AI in the Azure ecosystem.
* Demonstrate the ability to learn new technologies and stay current with Azure advancements; meet security screening requirements as needed (Microsoft Cloud Background Check on hire/transfer and every two years).
Qualifications
* Bachelor's degree in computer science or a related technical field.
* Engineering experience with programming in languages such as C#, Java, JavaScript, or Python.
* Broad knowledge of cloud computing and hands-on experience building cloud applications (Web and IoT) with scalable microservices; experience with end-to-end monitoring/observability and CI/CD pipelines (blue/green or canary).
* Proficiency with containerized deployments and Kubernetes orchestration.
* Strong technical curiosity and ability to stay current with Azure platform innovations and broader cloud trends.
* Relational database migrations (SQL Server and OSS databases) and Open Source relational databases (MySQL, MariaDB, PostgreSQL) in Azure context; experience with Azure Cosmos DB.
* Experience with structured and unstructured data in Big Data scenarios (SQL Data Warehouse, Snowflake, BigQuery, Redshift, data lake concepts).
* Advanced Analytics using Databricks and Spark; streaming workloads with Spark Streaming, Flink, Kafka Streams, and Storm; AI using Azure AI ecosystem.
* Security screening capability and willingness to meet Microsoft, customer, and/or government requirements as applicable.
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