Software Engineer II - Finance Data & Experiences

Microsoft•Redmond, WA

22h•$102,100 - $219,200

About The Position

The Finance Data & Experiences (FD&E) organization is on a mission to redefine how Microsoft measures, monitors, and optimizes its global business. This role offers a unique opportunity to lead with bold ideas, apply cutting-edge technology, and work across Finance, Sales, Marketing, Business Operations, and Product Engineering to deliver high-impact business solutions. The ideal candidate will thrive in fast-paced, cross-functional environments, bring fresh thinking to complex problems, and be eager to learn, take ownership of end-to-end processes, and deliver outcomes. At FD&E, you will help build reliable, scalable, and secure data solutions that power decision-making, business insights, automation, and AI-driven experiences. You will work across data engineering and software engineering disciplines, contributing to data pipelines, data platforms, services, analytics products, and engineering systems that support Microsoft’s global business. 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.

Requirements

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.
Demonstrated ability to collaborate effectively across disciplines, communicate clearly, and learn quickly in a fast-paced environment.
Demonstrated curiosity, ownership, and comfort working through ambiguity while delivering results with guidance from engineers.

Nice To Haves

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 with cloud-scale data platforms, distributed data processing, data warehousing, lakehouse architectures, or modern analytics platforms.
Experience designing, building, testing, and maintaining data pipelines, data processing jobs, data models, APIs, services, or related engineering systems.
Experience with ETL/ELT processes, orchestration, telemetry, monitoring, CI/CD, automated testing, and operational support for production systems.
Experience building solutions that enable AI, machine learning, business intelligence, reporting, experimentation, or data-driven decision making.
Familiarity with Azure data technologies and analytics platforms such as Microsoft Fabric, Synapse Analytics, Databricks, Spark, Cosmos DB, SQL, Kusto, or similar technologies.
Proficiency in SQL and at least one general-purpose programming language such as Python, C#, Java, or Scala.
Understanding of software engineering fundamentals, including data structures, algorithms, source control, testing, debugging, and code reviews.
Understanding of data quality, reliability, privacy, security, and governance considerations for production environments.

Responsibilities

Design, build, test, and maintain reliable data pipelines, data transformations, and data services that support business reporting, analytics, AI, and product experiences.
Partner with stakeholders across Finance, Sales, Marketing, Business Operations, and Product Engineering to understand requirements and translate them into clear, incremental technical deliverables.
Develop and maintain code, data processing logic, and automation using modern engineering practices, with a focus on extensibility, maintainability, reliability, and testability.
Explore design options for data and software solutions, document tradeoffs, and incorporate feedback from more experienced engineers and partner teams.
Build and improve data quality checks, validation, monitoring, and telemetry to detect issues early and improve trust in business-critical data assets.
Participate in code reviews and data pipeline reviews to ensure solutions meet team standards, include appropriate test coverage, and consider diagnosability, reliability, privacy, security, and maintainability.
Contribute to secure-by-design data solutions by applying privacy, compliance, access control, and security best practices for data movement, storage, and consumption.
Use AI tools and disciplined engineering practices to improve productivity, quality, documentation, testing, and supportability across the software development lifecycle.