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# Software Engineer II

- **Company:** Microsoft
- **Location:** Redmond, WA, United States
- **Experience:** Experienced
- **Salary:** $102,100.0 - $202,200.0
- **Contract:** Permanent contract
- **Skills:** Training Data, C (Programming Language), Java (Programming Language), JavaScript (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Application Frameworks, Automation of Tests, Microsoft Azure, C Sharp (Programming Language), C++ (Programming Language), Cloud Computing, Code Generation, Continuous Integration, Data Architecture, Information Engineering, Data Infrastructure, Data Structures, Data Systems, Distributed Data Store, Distributed Systems, Python (Programming Language), Marketing Information Systems, Metadata, Meta-Data Management, Metadata Repositories, Software Product Management, DataOps, Software Engineering, Data Classification, Data Ingestion, Azure Data Factory, Apache Spark, Generative AI, Agentic-AI, Git, Event Driven Architecture, Microsoft Fabric, Information Technology, Data Lineage, Cosmos DB, Data Management, Azure Synapse Analytics, Data Pipelines, Databricks, Microservices
- **Published:** October 6, 2026
- **Apply:** https://www.jobmonkeyjobs.com/career/28088529/Software-Engineer-Ii-Washington-Redmond-1210

## About the Role

* 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., * 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.

Software Engineering IC3 - The typical base pay range for this role across the U.S. is USD $102,100 - $202,200 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $133,800 - $219,200 per year.

## Description

* 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.