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Mid-level Data Engineer in Bengaluru with common tech stack and mid-experience attracts strong applicant competition.
Requires Azure/Databricks platform experience, moderately limiting cross-industry portability.
Requires explicit 4–8 years and mandatory Databricks, PySpark, and Azure skills, enforcing rigid shortlisting.
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Design, build, and optimize scalable data pipelines and ETL/ELT workflows using Databricks, Azure Data Factory, Microsoft Fabric, PySpark, and SQL.
Architect and implement data Lakehouse and data warehouse solutions on Databricks and Microsoft Fabric platforms.
Ensure robust data operations by collaborating with data scientists and analysts, enforcing data governance, security, and leveraging CI/CD and IaC for pipeline deployment and maintenance.
4-8 years of experience in data engineering with strong knowledge of cloud data platforms.
Proficiency in PySpark, Azure Data Factory, Databricks, Microsoft Fabric, and SQL development including complex queries and stored procedures.
Bachelor’s or Master’s degree in Computer Science, Information Systems, Engineering, or related field.
Experience with data lakehouse and data warehouse architectures, Delta Lake, Synapse Analytics, and CI/CD pipelines with version control tools like Git and deployment automation.
Experienced in building scalable, high-performance data solutions on modern cloud platforms, specifically Microsoft Fabric and Databricks.
Capable of handling end-to-end data engineering responsibilities including architecture, development, automation, security, and compliance.
Able to collaborate cross-functionally with business analysts, data scientists, and engineering teams to enable real-time, secure, and reliable data delivery.