Responsibilities
Design, develop, test, deploy, and operate scalable cloud-based applications, data platforms, analytics solutions, automation capabilities, and AI-powered experiences using modern Microsoft technologies.
Independently deliver features and components through design, implementation, testing, deployment, monitoring, and operational support with minimal guidance.
Use AI tools and practices responsibly throughout the software development lifecycle to improve engineering productivity, solution quality, testing, debugging, and operational effectiveness.
Apply engineering fundamentals to build high-quality, maintainable, secure, and well-tested solutions while improving reliability, scalability, performance, and observability.
Develop and execute test strategies for assigned features, leveraging automated testing and AI-assisted testing tools to improve quality, prevent regressions, and validate security requirements.
Create technical designs and specifications for scoped features, incorporating telemetry, monitoring, security, compliance, resiliency, and operational considerations.
Design, build, and optimize data pipelines, semantic models, data products, analytics solutions, and AI-enabled capabilities that drive business insights and decision making.
Analyze production issues, troubleshoot complex problems, conduct root cause analysis, and leverage telemetry and diagnostics to improve service reliability and customer experience.
Collaborate with engineers, product managers, data scientists, and business stakeholders to understand requirements, identify dependencies, and deliver integrated customer-focused solutions.
Contribute to architecture and design discussions by evaluating design alternatives, documenting tradeoffs, providing feedback on solution architecture, and owning design decisions within assigned feature areas.
Apply secure engineering practices and participate in security, privacy, compliance, accessibility, and responsible AI reviews to ensure solutions meet Microsoft standards.
Drive engineering excellence through code reviews, automated testing, CI/CD practices, operational rigor, reusable solutions, and continuous improvement.
Participate in live-site operations, on-call support, incident response, and deployment activities while continuously improving monitoring, automation, troubleshooting guidance, and operational readiness.
Mentor engineers through knowledge sharing, technical guidance, and peer reviews while fostering an inclusive, collaborative, and growth-oriented engineering culture.
Qualifications
Required Qualifications
Bachelor's Degree in Computer Science or related technical field AND 2+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience.
Preferred Qualifications
Master's Degree in Computer Science or related technical field AND 3+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python
OR Bachelor's Degree in Computer Science or related technical field AND 5+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python
OR equivalent experience.
Experience in software engineering, business analytics, data science, data engineering, business intelligence, data modeling, semantic modeling, or related technical disciplines.
Experience developing, testing, deploying, and supporting cloud-based applications, data platforms, analytics solutions, data pipelines, semantic models, and AI-powered solutions.
Experience building data, analytics, automation, reporting, business intelligence, and AI solutions that support business-critical workloads.
Experience with Microsoft Azure, Microsoft Fabric, Power BI, Azure AI Services, Azure OpenAI, Azure Data Factory, Synapse Analytics, Dataverse, and related cloud technologies.
Knowledge of data warehousing, dimensional modeling, semantic modeling, distributed systems, cloud-native architectures, API development, telemetry, monitoring, resiliency, operational excellence, and DevOps practices.
Experience with software engineering lifecycle practices, including architecture and design reviews, source control, testing, CI/CD, monitoring, and telemetry.
Familiarity with AI/ML development, prompt engineering, agentic frameworks, GitHub Copilot, AI-assisted development tools, and Responsible AI practices.
Experience working in Agile development environments and collaborating with cross-functional engineering teams.
Demonstrated ability to leverage AI tools and services to improve engineering productivity, solution quality, and business outcomes.
Problem-solving, communication, collaboration, customer-focused mindset, and commitment to continuous learning.
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.
