Software Engineer II

Microsoft•Redmond, WA

2d•$102,100 - $202,200

About The Position

Imagine being at the forefront of a transformation powered by Data and AI, helping Marketing at Microsoft become a "Frontier Organization" by modernizing how data is built, governed, discovered, and consumed. As a Software Engineer II on the Global Marketing Data Engineering team, you will help build the next generation of Marketing data platform capabilities using Microsoft Fabric, OneLake, Azure, and AI-native engineering patterns. This role will work on reusable platform capabilities that make data easier to discover, trust, govern, access, operate, and consume across Marketing. You will contribute to modernizing the data estate through Fabric adoption, governed data products, metadata-driven engineering, data quality, observability, self-service capabilities, and AI-assisted development. You will also help evolve shared platform capabilities that enable teams to move away from fragmented and bespoke implementations toward standardized, reusable engineering patterns. This is a hands-on software engineering role for someone who enjoys building modern data platforms, experimenting with emerging AI capabilities, and translating platform architecture into scalable production solutions. 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.

Nice To Haves

Experience with software engineering fundamentals, including data structures, APIs, distributed systems concepts, testing, and production-quality software development.
Experience developing or operating data platforms, data pipelines, distributed data-processing systems, cloud applications, microservices, or event-driven architectures.
Experience with Microsoft Azure or comparable cloud platforms.
Experience with modern data technologies such as Microsoft Fabric, OneLake, Lakehouse, Spark, Azure Data Factory, Synapse, Databricks, Cosmos DB, Azure Data Explorer, or equivalent technologies.
Experience developing data ingestion, transformation, modeling, or publishing solutions, including reusable data-engineering frameworks, APIs, services, or internal platform capabilities.
Experience with metadata-driven or configuration-driven data platforms and governance technologies such as Microsoft Purview, data catalogs, data lineage, and data classification.
Experience using Git-based development, automated testing, CI/CD, and modern software-development practices.
Experience with generative AI, agents, MCP, semantic/ontology models, AI-ready data-product patterns, and applying AI and automation to data-engineering workflows.

Responsibilities

Design, develop, and operate modern data platform capabilities using Microsoft Fabric, OneLake, Azure, and related technologies.
Build reusable frameworks and services for data ingestion, transformation, publishing, and data-product engineering, reducing bespoke implementations across teams.
Help modernize existing workloads and data pipelines onto Microsoft Fabric and governed Lakehouse architecture.
Develop platform capabilities that improve data discoverability, metadata management, ownership, lineage, readiness, quality, health, and access experiences.
Build and enhance shared platform capabilities supporting the broader Marketing data control-plane strategy.
Develop metadata-driven and configuration-driven engineering frameworks that reduce manual development and accelerate onboarding of new data products.
Apply AI-assisted and agentic engineering techniques to code generation, migration, testing, documentation, metadata generation, schema mapping, and other data-engineering workflows.
Explore and implement patterns for exposing trusted data and metadata to AI agents, MCP-based services, ontology-driven experiences, and other AI applications.
Build reusable APIs, microservices, workers, and platform components that can be adopted across multiple Marketing data scenarios.
Develop automated capabilities for data quality validation, testing, schema enforcement, monitoring, and operational health.
Partner with Data Engineering, Platform Engineering, DataOps, Security/Governance, and product teams to deliver end-to-end platform solutions.
Work with Microsoft Fabric, Purview, Azure, and AI product teams to evaluate emerging capabilities and integrate appropriate technologies into the Marketing data ecosystem.
Use telemetry, customer feedback, incidents, and usage data to continuously improve platform capabilities.
Embody Microsoft’s culture and values.