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Bangalore mid-level role with strong demand but niche Databricks/Snowflake skills, moderate competition.
Platform-specific Databricks, Snowflake, PySpark, and Azure requirements increase industry-specific skill sensitivity.
Explicit 4+ years and mandatory Databricks, Snowflake, PySpark, and Azure skills create strict filters.
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Develop, optimize, and maintain large-scale data pipelines and ELT workflows across Databricks and Snowflake platforms.
Design and implement scalable PySpark applications, Snowflake SQL optimizations, and Azure Data Factory integrations to support analytics and enterprise data initiatives.
Collaborate closely with stakeholders to meet data requirements, ensure data governance compliance, and troubleshoot pipeline or platform issues for reliable data operations.
Bachelor's degree in Computer Science, IT, or related field, or equivalent experience.
4+ years of experience in data engineering or big data development.
3+ years hands-on experience with Databricks, PySpark, Delta Lake, and Azure Data Engineering services.
3+ years hands-on experience with Snowflake SQL, Snowpipe, Streams, Tasks, and ELT pipeline development.
Deep expertise in cloud data engineering focused on both Databricks and Snowflake ecosystems.
Experience managing and tuning complex ETL pipelines and cloud warehouses for performance and cost efficiency.
Proficient in collaborative agile environments working with cross-functional teams including data engineers, architects, and business stakeholders.