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Generalist data title, 3+ years requirement, and Bangalore metro increase applicant competition.
Data engineering skills transfer across industries, but Databricks specialization raises domain sensitivity.
Explicit 3+ years plus mandatory Databricks, PySpark, Delta Lake tighten shortlisting.
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Design and develop scalable data pipelines and Lakehouse solutions on Databricks with performance and cost optimization.
Implement and manage Unity Catalog for data governance including access control, lineage, and security.
Build monitoring and automation using Databricks-native AI to enable self-healing operations and integrate with CI/CD workflows.
Bachelor’s or Master’s degree in Computer Science, Information Technology or equivalent experience.
Minimum 3 years of data engineering experience with at least 1 year of hands-on Databricks experience in enterprise environments.
Proficient in Databricks Lakehouse architecture, Delta Lake, Unity Catalog, Spark workload tuning, Python (PySpark), SQL, and CI/CD DevOps principles.
Experience with observability tooling for Databricks is mandatory.
Experienced in performance engineering focused on cost and reliability within Databricks environments.
Competent with operationalizing AI-assisted automation and monitoring for data platforms.
Ability to independently deliver and maintain production data pipelines and governance solutions within enterprise settings.