Data Engineer 2

Data Engineer - Office Platform 

Microsoft IDC - Bengaluru, India 

Profession: Software Engineering 

Discipline: Data Engineering 

Microsoft is a global leader in software, services, devices and solutions that empower every person and every organization on the planet to achieve more. Our mission is to enable people and businesses throughout the world to realize their full potential by creating technology that transforms the way people work, play, and communicate. We develop and market software, services, and hardware that deliver new opportunities, greater convenience, and enhanced value to people's lives. We do business worldwide and have offices in more than 100 countries. 

We are looking for a Data Engineer to join our Office Platform team, for building our M365 developer program. You will be part of a dynamic and diverse team that works on cutting-edge technologies and delivers innovative solutions that empower millions of developers around the world. You will work on challenging and complex problems that require creativity, collaboration, and a growth mindset. You will design and develop high quality, resilient and easily maintainable software that enhances developer experience and drives business value. 

The ideal candidate would have the following experiences and skills: 

• Bachelor's degree in computer science, Math, Software Engineering, Computer Engineering, or related field AND 5+ years’ experience in business analytics, data science, software development, data modeling or data engineering work 

OR master’s degree in computer science, Math, Software Engineering, Computer Engineering, or related field AND 3+ years of business analytics, data science, software development, data modeling or data engineering work experience 

• Experience in C#/Java. 

• Excellent Data Engineering skills 

• Demonstrate a growth mindset and a passion for learning new technologies. 

• Excellent communication, collaboration, and problem-solving skills. 

• Experience with agile development methodologies, such as Scrum. 

Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances.  We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you need assistance and/or a reasonable accommodation due to a disability during the application or the recruiting process, please send a request via the Accommodation request form.

Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.

Your responsibilities will include: 

• Data Requirements and Modeling: Collaborate with stakeholders, document data requirements, evaluate data costs and feasibility, negotiate data agreements, and propose data metrics for project-relevant features. 
• Data Model Design and Specification: Contribute to the data model design, draft design specification documents, improve data schemas, and balance analytical requirements and compute/storage consumption for data. 
• Data Engineering:
• Data Extraction and Validation: Implement code to extract raw data from upstream sources, perform code reviews, implement orchestration techniques, validate data quality and reliability, and record data source control and versioning. 
• Data Transformation and Merging: Apply standard operations to transform raw data into compatible forms, use software and tools to wrangle and analyze data, and merge data into distributed systems or products. 
• Data Tool Design and Maintenance: Design and maintain data tools that are used to transform, manage, and access data, write efficient code to test and validate data platforms, and implement sustainable design patterns. 
• Data Monitoring and Troubleshooting: Follow performance monitoring protocols, build visualizations and aggregations to monitor data quality and pipeline health, troubleshoot and fix problems or anomalies, and document and share insights. 
• Data Compliance and Governance: Follow data modeling and handling procedures to comply with laws and policies, tag and classify data, govern data accessibility and traceability, and contribute to the data glossary.