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Tier-1 brand, metro location, and mid-level generalist data role increase applicant competition.
Databricks-focused data engineering skills are moderately transferable across industries but require platform-specific expertise.
Explicit 5+ years requirement and mandatory Databricks/PySpark/cloud skills raise shortlisting strictness.
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Design, develop, and maintain scalable data engineering solutions using Databricks, PySpark, and SQL on cloud platforms (Azure, AWS, or GCP).
Implement and optimize secure, scalable data architectures and pipelines including Delta Lake, Delta Live Tables, Unity Catalog, and Medallion Framework to drive data-driven decision-making.
Manage Databricks clusters, monitor performance, troubleshoot production incidents, and collaborate with stakeholders to translate business requirements into technical solutions.
5+ years of relevant experience in data engineering with hands-on expertise in Databricks, PySpark, SQL, and cloud platforms (Azure, AWS, or GCP).
Experience with Delta Lake, Delta Live Tables, Unity Catalog/Data Governance, Databricks Workflows, and Serverless Compute mandatory.
Bachelor’s or master’s degree in any field.
Familiarity with GitHub, CI/CD pipelines, Agile methodologies, and DevOps practices.
Strong technical operator with proven ability to build and optimize data platforms on Databricks in cloud environments, emphasizing performance and scalability.
Experienced in applying Lakehouse, Medallion, and data warehousing architectural standards at enterprise scale.
Capable of handling end-to-end responsibilities including data governance, security, and compliance in complex data engineering projects.