M

Microsoft

Builds workplace software, PCs and cloud services

Data Engineer

Data EngineeringPosted on Nov 12
Full-time$102.1k - $219.2k /yr

About the Job

Requirements

  • A Master's degree in Computer Science, Mathematics, Software Engineering, Computer Engineering, or a related field and at least one year of experience in business analytics, data science, software development, data modeling, or data engineering; or a Bachelor's degree in one of those fields and at least two years of such experience; or equivalent experience.
  • Ability to meet Microsoft, customer, and/or government security screening requirements, including passing the Microsoft Cloud Background Check upon hire or transfer and every two years thereafter.

Responsibilities

  • Design, develop, test, and maintain secure, scalable data pipelines and processing solutions supporting UDP and enterprise analytics workloads.
  • Develop data engineering solutions using PySpark, SQL, Spark notebooks, and distributed data processing technologies across Microsoft Fabric and Azure Synapse environments.
  • Build and maintain curated data models and reusable datasets, applying dimensional modeling, data transformation, and data architecture practices.
  • Implement automated data quality, validation, monitoring, and production support capabilities to ensure reliable and trustworthy data products.
  • Optimize data pipelines and processing workloads for performance, scalability, reliability, and efficient resource utilization.
  • Apply engineering best practices including source control, code reviews, testing, CI/CD, documentation, and maintainable development patterns.
  • Implement appropriate security, privacy, access controls, and data governance requirements when processing sensitive enterprise and customer data.
  • Troubleshoot data pipeline, transformation, and production issues, perform root-cause analysis, and implement durable fixes.
  • Partner with analysts, engineering teams, and business stakeholders to translate reporting and analytics requirements into data solutions, communicate progress and technical tradeoffs, and resolve data issues.
  • Contribute to continuous improvement of the UDP engineering platform by identifying opportunities to simplify pipelines, improve data architecture, increase reuse, and reduce operational complexity.
  • Embody Microsoft's culture and values.

Desired Qualifications

  • A Master's degree in Computer Science, Mathematics, Software Engineering, Computer Engineering, or a related field and at least three years of experience in business analytics, data science, software development, data modeling, or data engineering; or a Bachelor's degree in one of those fields and at least five years of such experience; or equivalent experience.
  • At least one year of experience with data governance, data compliance, and/or data security.
  • At least three years of experience in data or analytics engineering, building and supporting production data solutions.
  • Experience developing Apache Spark/PySpark notebooks for large-scale data ingestion, transformation, enrichment, and processing.
  • Experience with Azure Synapse Analytics or similar distributed data platforms, including secure ETL and data-processing workloads.
  • Proficiency in SQL and dimensional data modeling, transforming complex source data into curated datasets optimized for analytics and Power BI.
  • Experience building reliable production data pipelines, including validation, error handling, performance optimization, monitoring, and troubleshooting.
  • Ability to translate business and reporting requirements into scalable data solutions and collaborate across data engineering, BI, analytics, and architecture teams.
  • Hands-on experience with Microsoft Fabric Data Engineering, including Lakehouses, notebooks, Delta tables, OneLake, and SQL analytics endpoints.
  • Experience designing medallion/lakehouse architectures across raw, curated, and consumption-ready data layers.
  • Understanding of enterprise data security and governance, including identity-based access, environment separation, and handling sensitive data.
  • Experience with software engineering and DevOps practices for data solutions, including Git, code reviews, testing, CI/CD, and deployment across development, UAT, and production.
  • Experience using AI-assisted development tools and reusable AI skills to improve data engineering productivity, code quality, testing, and troubleshooting.

About the Company

Microsoft

Builds workplace software, PCs and cloud services

Microsoft builds workplace software, operating systems and cloud infrastructure for consumers, businesses and government agencies, from small organizations to global enterprises. Microsoft 365 combines Word and Excel with Teams communication and Copilot AI features, while Windows runs PCs and Surface supplies the company's own computers. Azure rents computing capacity, storage and databases to build and run web applications. Microsoft also sells Xbox consoles and games, collecting revenue through software licenses, subscriptions, usage charges and product sales. Founded in 1975 by Bill Gates and Paul Allen, Microsoft is headquartered in Redmond, Washington.

Company size
10,001+
Company stage
IPO
Headquarters
Redmond, WA
Founded
1975

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