Microsoft

Data Engineer II - Getting Customers Ready for AI

Microsoft$102K — $202K *
Information Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Bachelor's Degree in Computer Science or related field and 2+ years of software, data, or related engineering experience.
  • Proficiency in programming languages such as C, C++, C#, Java, JavaScript, or Python.
  • Hands-on experience in building or maintaining data pipelines and distributed data systems preferred.
  • Understanding of data modeling and ETL processes is advantageous.
  • Familiarity with cloud-based data platforms, ideally Azure, is a plus.

Responsibilities

  • Design and build scalable data pipelines to process security and operational data.
  • Develop and optimize ETL/ELT workflows for transforming telemetry into structured data.
  • Implement data ingestion frameworks for multi-source integration.
  • Improve the performance and reliability of data pipelines using optimization techniques.
  • Collaborate with AI engineers to ensure data is optimized for AI workflows.
  • Build telemetry pipelines that provide insights into AI system performance.
  • Contribute to cross-team integration and data solutions delivery.

Benefits

  • Access to a comprehensive benefits package including health, dental, and vision insurance.
  • Opportunities for professional development and training.
  • Flexible work arrangements promoting work-life balance.
  • Supportive work culture valuing diversity and inclusion.
Full Job Description
Overview

Microsoft Security's Getting Customers Ready for AI team is seeking a Data Engineer II to help build the data foundations that power AI-native security systems.

In this role, you will design and develop scalable data platforms, pipelines, and telemetry systems that transform raw signals across identity, devices, data, applications, and infrastructure into high-quality, trusted datasets for analytics and AI-driven insights.

You will work in a collaborative engineering environment to deliver reliable, secure, and performant data systems, enabling downstream AI models, security detections, and customer-facing experiences. This role is ideal for engineers looking to deepen their expertise in large-scale data systems, distributed processing, and modern data platform architectures for AI and Agents.

Responsibilities

Data Platform & Pipeline Engineering

  • Design and build scalable data pipelines (batch and streaming) to process large volumes of security and operational data.


  • Develop and optimize ETL/ELT workflows that transform raw telemetry into structured, consumable datasets.


  • Implement data ingestion frameworks to integrate multi-source data from services, APIs, and event streams.


  • Improve pipeline performance, reliability, and efficiency through partitioning, indexing, and optimization techniques.


Data Modeling & Storage Systems

  • Design and evolve data models, schemas, and storage strategies for analytics and AI use cases.


  • Work with distributed storage systems (e.g., data lakes, warehouses) to ensure scalability and cost efficiency.


  • Maintain data partitioning, retention, and lifecycle strategies aligned to business and compliance needs.


  • Ensure data is structured for downstream ML pipelines, feature engineering, and analytics workloads.


Data Quality, Governance & Security

  • Implement data validation, quality checks, and observability frameworks to ensure data accuracy and reliability.


  • Apply best practices for data governance, lineage, and auditing across pipelines and datasets.


  • Ensure compliance with security, privacy, and regulatory requirements when handling sensitive data.


  • Contribute to standardization of data contracts and schemas across services.


AI Readiness & Intelligence Enablement

  • Enable high-quality datasets for AI/ML teams, including support for feature pipelines and training data preparation.


  • Collaborate with AI engineers to ensure data is optimized for RAG pipelines, model training, and evaluation workflows.


  • Build and maintain telemetry pipelines and metrics systems that provide insights into AI system performance and usage.


  • Support development of data-driven signals and insights that improve customer security posture.


Collaboration & Execution

  • Partner with engineering, data science, and product teams to deliver end-to-end data solutions.


  • Contribute to system design discussions, architecture reviews, and cross-team integration efforts.


  • Work across teams to ensure consistent data definitions and interoperability across platforms.


Engineering Excellence

  • Write clean, maintainable, and well-tested code for data pipelines and platform services.


  • Build monitoring and alerting mechanisms for pipeline health, latency, and data quality issues.


  • Document data architecture, pipeline designs, and operational practices for knowledge sharing and scalability.


  • Follow best practices for performance optimization, cost management, and reliability engineering.
  • Embody our culture and values.


Qualifications

Required Qualifications

  • Bachelor's Degree in Computer Science or related technical field AND 2+ years of software, data, or related engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python
    • OR equivalent experience


Other Requirements: Ability to meet Microsoft, customer, and/or government security screening requirements are required for this role. These requirements include but are not limited to the following specialized security screenings:

    • Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years.


Preferred Qualifications:

  • Hands-on experience building or maintaining data pipelines and distributed data systems.


  • Programming experience in Python, Scala, or SQL for data processing and pipeline development.
  • Understanding of data modeling, ETL processes, and large-scale data processing concepts.
  • Experience with big data frameworks (e.g., Spark, Flink) or streaming systems (e.g., Kafka/Event Hub).
  • Familiarity with cloud-based data platforms (Azure preferred, e.g., ADLS, Synapse, Databricks).
  • Exposure to data governance, security, and compliance practices in enterprise environments.
  • Experience supporting AI/ML workloads through data pipelines, feature stores, or training datasets.
  • Developed problem-solving skills with the ability to operate in ambiguity and deliver incrementally.


#MSFTSecurity

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.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
https://careers.microsoft.com/us/en/us-corporate-pay

This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.

About Microsoft

Microsoft is an American multinational corporation that develops, manufactures, licenses, supports, and sells a range of software products and services. Microsoft’s devices and consumer (D&C) licensing segment licenses the Windows operating system and related software, Microsoft Office for consumers, and the Windows Phone operating system. The company’s computing and gaming hardware segment provides Xbox gaming and entertainment consoles and accessories, second-party and third-party video games, and Xbox Live subscriptions; surface devices and accessories; and Microsoft PC accessories. Its phone hardware segment offers Lumia smartphones and other non-Lumia phones. Its D&C segment provides Windows Store, Xbox Live transactions, and Windows phone store; search advertising; display advertising; Office 365 Home and Office 365 Personal; first-party video games; and other consumer products and services as well as operating retail stores. Microsoft’s commercial licensing segments license server products, including Windows Server, Microsoft SQL Server, Visual Studio, System Center, and related Client Access Licenses (CALs); Windows Embedded; Windows operating system; Microsoft Office for business, including Office, Exchange, SharePoint, Lync, and related CALs; Microsoft Dynamics business solutions; and Skype. Its commercial segment offers enterprise services, including premier support services and Microsoft consulting services; commercial cloud comprising Office 365 Commercial, other Microsoft Office online offerings, Dynamics CRM Online, and Microsoft Azure; and other commercial products and online services. The company markets and distributes its products through original equipment manufacturers, distributors, and resellers, as well as online.

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Learn more about Microsoft
Size
181,000 employees
Market Cap
$1,762.4 billion
Industry
Net Income
$51.3 billion
Founded
1975
5 Year Trend
+15.5%
Revenue
$153.2 billion
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