Data Engineer

Job Description

Overview

With more than 45,000 employees and partners worldwide, the Customer Experience and Success (CE&S) organization is on a mission to empower customers to accelerate business value through differentiated customer experiences that leverage Microsoft’s products and services, ignited by our people and culture. We drive cross-company alignment and execution, ensuring that we consistently exceed customers’ expectations in every interaction, whether in-product, digital, or human-centered. CE&S is responsible for all up services across the company, including consulting, customer success, and support across Microsoft’s portfolio of solutions and products. Join CE&S and help us accelerate AI transformation for our customers and the world.

Within CE&S, the Customer Service & Support (CSS) organization builds trust and confidence for every person and organization through delivering a seamless support experience. In CSS, we are powered by Microsoft’s AI technology to help consumers, businesses, partners, and more, resolve their issues quickly and securely, helping prevent future problems from occurring and achieving more from their Microsoft investment.

We are seeking a skilled Data Engineer to design, develop, and maintain scalable data pipelines, data models, and enterprise data warehouse components that power advanced analytics and reporting across the organization. This role focuses on sourcing, transforming, integrating, and modelling data to create a trusted foundation for analytics, reporting, and operational insight generation.

The ideal candidate will have hands-on experience with ETL/ELT development, SQL-based data manipulation, and modern data warehouse modelling principles, along with a solid understanding of Microsoft Azure and Fabric data services. As a Data Engineer, you will build high-quality data flows, optimize pipeline performance, ensure the reliability of mission-critical datasets, and collaborate closely with data analytics and engineering teams to transform raw data into actionable insights.

This role is flexible in that you can work up to 50% from home.

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.

Responsibilities

Data Engineering (ETL/ELT Development)
• Design, develop, and maintain scalable data pipelines to support ingestion, cleansing, transformation, and preparation of data for analysis, reporting, and AI model training.
• Build frameworks to validate data quality and completeness, detect anomalies, strengthen pipeline resilience, and support testing.
• Design and implement end-to-end data lifecycle processes—including architecture, development, deployment, monitoring, and recovery.
• Source and integrate data from diverse systems (APIs, operational tools, flat files, SQL Server, cloud sources, etc.) ensuring completeness, integrity, and reliability.
• Utilize Azure/Fabric data services to orchestrate and automate data flows
• Implement monitoring, logging, alerting, and telemetry to ensure timely and reliable pipeline execution.
Performance Monitoring & Optimization
• Implement automated performance monitoring across pipelines, including building dashboards and aggregations to assess pipeline health.
• Optimize pipelines, queries, and workloads for efficiency, scalability, and cost-effectiveness within Azure/Fabric environments.
• Conduct database administration tasks such as performance tuning, maintenance, indexing, and capacity monitoring.
Innovation & Continuous Improvement
• Evaluate emerging technologies and contribute to architectural decisions that shape next-generation data platforms.
• Identify opportunities to streamline data processes, improve data accessibility, and enhance engineering best practices.
• Continuously improve ETL pipelines and workflows to align with evolving business and technical requirements.
Data Warehouse Modelling
• Design and maintain dimensional models and modern analytics-ready schemas using modular, scalable modelling techniques.
• Identify, define, and standardize business metrics and measures, transforming raw data into fact and dimension structures.
• Relate data across disparate systems using natural keys and engineered relationships (e.g., surrogate keys, time intelligence).
• Build semantic layers and curated datasets for analytics teams, BI developers, and Power BI consumers.
• Ensure models support flexible slice-and-dice analytics, high query performance, and Microsoft best practices.
Data Quality, Governance & Security
• Anticipate and embed data governance requirements within data modelling and data handling practices.
• Establish and enforce standards for data integrity, lineage, naming conventions, and metadata management.
• Implement robust security controls, access policies, and data protection measures in compliance with enterprise and legal requirements.
• Collaborate with data stewards and SMEs to validate data definitions, transformation logic, and quality rules.
• Produce documentation for pipelines, schemas, data flows, and operational procedures.
Collaboration & Cross-Functional Alignment
• Work closely with Data Analysts, Data Scientists, Power BI Developers, and business partners to understand data needs and deliver reliable, scalable solutions.
• Collaborate with internal teams to understand how data flows through other internal data sources to ensure consistency across reporting, and ensure sources created/used mirror other sources used.
• Collaborate with engineering teams to ensure alignment with existing data sources, architectural patterns, and reporting practices.
• Provide input on cloud architecture, optimization strategies, and data engineering best practices.
• Troubleshoot, optimize, and enhance pipelines and models to improve reliability, agility, and performance.

Qualifications

Required Qualifications:

• Bachelor’s Degree in Computer Science, Mathematics, Software Engineering, Computer Engineering, or related field AND 2+ years’ experience in business analytics, data science, software development, data modelling, or data engineering; OR
  Master’s Degree in a related field AND 1+ year of relevant experience; OR equivalent professional experience.
• Hands On experience in software or data engineering with proficiency in C#, Java, or equivalent programming languages.
• Strong working knowledge in SQL or KQL for data retrieval, transformation, and manipulation.
• Working experience with ETL/ELT and cloud data technologies including:
  o Azure Data Lake / ADLS Gen2
  o Azure Data Factory / Synapse Pipelines
  o Azure Synapse Analytics
  o Azure Logic Apps
  o Azure Functions
  o Azure Data Explorer (Kusto)
  o Power BI / Fabric Dataflows (preferred)
• Proficiency in SQL development (queries, joins, transformations, stored procedures, performance tuning).
• Experience with Microsoft data platforms such as Azure SQL Database, SQL Server, and Azure Storage services.
• Strong understanding of ETL concepts, data integration patterns, and cloud-based data engineering.
• Experience with data warehouse modelling (fact/dimension schemas, measures, time-based modelling).
• Familiarity with data governance, data quality frameworks, and security best practices.

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 thereafter.

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

Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.