Senior Data Engineer at Microsoft

Redmond, Washington, United States -

Full Time

Start Date

Immediate

Expiry Date

20 Feb, 26

Salary

0.0

Posted On

22 Nov, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Architecture, ETL, ELT, Spark, Azure Data Lake, Synapse, Data Integrity, Data Lineage, Compliance, Power BI, Data Modeling, Machine Learning, Data Security, Privacy Compliance, Governance Frameworks, Collaboration, Problem Solving

Industry

Software Development

Description

Data Architecture & Pipeline Development Design and implement robust ETL/ELT workflows for structured and unstructured data using modern data engineering frameworks. Build distributed data processing systems leveraging technologies such as Spark, Azure Data Lake, and Synapse. Establish standards for data integrity, lineage, and compliance with enterprise security and privacy policies. Develop and maintain low/no-code dashboards and data-driven apps (e.g., Power BI, Vibe-coded apps) to enable self-service analytics for stakeholders. Evaluate emerging technologies and contribute to architectural decisions for next-generation data platforms. Master's Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field AND 3+ years experience in business analytics, data science, software development, data modeling, or data engineering OR Bachelor's Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field AND 4+ years experience in business analytics, data science, software development, data modeling, or data engineering OR equivalent experience. 3+ years experience in building distributed data processing systems leveraging technologies including, but not limited to, Spark, Azure Data Lake, or Synapse 5+ years of experience in data engineering or software development with a focus on large-scale data systems 2+ years experience developing and maintaining low/no-code dashboards and data-driven apps (e.g., Power BI, Vibe-coded apps) to enable self-service analytics for stakeholders Proficiency in managing machine learning data pipelines and feature engineering processes Proficiency in data security, privacy compliance, and governance frameworks. Demonstrate effective communication and collaboration skills in a dynamic, fast-paced environment Creativity, insightfulness, and sensitivity for a dynamic approach to problem-solving, combined with being motivated and self-driven, are essential

Responsibilities

Design and implement robust ETL/ELT workflows for structured and unstructured data. Evaluate emerging technologies and contribute to architectural decisions for next-generation data platforms.