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Mid-level Databricks data engineer in Bangalore, popular generalist role with broad skills, increasing competition.
Core Databricks, PySpark and SQL skills are highly transferable across industries, so background sensitivity is low.
Explicit 5–6 years plus mandatory Databricks, PySpark, and SQL requirements create high shortlisting strictness.
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Design, implement, and optimize large-scale ETL pipelines using Databricks and PySpark.
Develop and maintain complex SQL queries, stored procedures, and scalable data models for analytics.
Collaborate with stakeholders to build high-performance data solutions and ensure data quality across platforms.
5-6 years of data engineering experience with substantial hands-on expertise in Databricks and PySpark.
Advanced proficiency in Databricks platform, PySpark, and strong SQL skills including stored procedure maintenance.
Bachelor's degree in Computer Science, IT, or related field.
Work Experience Required: 5-6 years in data engineering explicitly mentioned.
Experienced in building and maintaining production-grade ETL pipelines in Databricks environments with distributed data processing expertise.
Ability to optimize data processing jobs for performance and troubleshoot complex data ingestion and transformation issues.
Familiarity with cloud data platforms (Azure Databricks or AWS Glue) and CI/CD for data workflows signals a competitive fit.