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Metro-based mid-level Azure Data Engineer with broad, popular skills increases applicant competition significantly.
Azure cloud and Databricks-specific tooling offers moderately transferable data engineering skills across industries.
Explicit 5-7 years requirement plus mandatory Azure Databricks, ADF, ADLS and SQL skills enforces strict filtering.
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Design, build, and optimize scalable data pipelines and platforms using Microsoft Azure data services.
Collaborate with data architects, analysts, data scientists, and business stakeholders to deliver secure and high-performing data solutions.
Implement and maintain ETL/ELT pipelines, data ingestion frameworks for batch and near real-time processing, and optimize data platform performance and cloud costs.
5-7 years total work experience with at least 4 years in Microsoft Azure Data Engineering.
Proven expertise with Azure Databricks, Azure Data Factory, Azure Data Lake Storage Gen2, Azure SQL Database, and Azure Blob Storage.
Experience in building ETL/ELT solutions for structured and semi-structured data and optimizing SQL performance.
Not explicitly mentioned in the JD: formal degree requirements, notice period, or mandatory onsite location constraints beyond Bangalore, KA, IN.
Experienced in designing and managing Azure cloud-native data engineering solutions with a focus on scalability and performance.
Strong background in developing reusable and metadata-driven data engineering frameworks and optimizing cloud resource usage.
Capable of collaborating across cross-functional teams including data architects, analysts, and scientists to align data solutions with business goals.