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Metro locations and common mid-senior Databricks data engineer skills create moderate applicant competition.
Databricks and PySpark skills transfer across industries, with moderate Azure platform specificity.
Explicit 6–10 years plus mandatory Azure Databricks, PySpark, and Azure stack make filters strict.
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Design and develop scalable data pipelines and ETL workflows using Azure Databricks, Python, and PySpark.
Optimize Spark jobs and ensure data quality, integrity, and governance within Azure ecosystem integrating with ADLS, ADF, and Synapse.
Collaborate with stakeholders to gather requirements and support AI/ML data pipelines, including integration of Large Language Models (LLMs).
6 to 10 years of experience in Azure Databricks engineering with strong Python and PySpark skills.
Proficiency in SQL, Azure Data Lake Storage (ADLS), Azure Data Factory (ADF), and Synapse.
Experience in building and optimizing ETL workflows and Spark job performance tuning.
Location requirement: Bangalore, Pune, or Chennai, India.
Experienced in designing and maintaining high-performance, scalable data engineering pipelines in Azure environment.
Skilled in integrating AI/ML workflows within data platforms, particularly with LLM-based use cases.
Capable of working closely with cross-functional teams for data solutions in enterprise-scale environments.