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PwC brand, Bangalore location, and mid-level data engineer experience attract many applicants despite Databricks specialization.
Databricks, PySpark and cloud engineering skills are broadly transferable across industries despite a healthcare preference.
Explicit 4-8 years requirement plus mandatory Databricks, PySpark, cloud and Spark tuning skills increase filter rigidity.
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Design and develop robust data engineering solutions on Databricks, including ETL/ELT pipelines and data integration.
Optimize and tune Spark performance to ensure efficient data processing within cloud environments (AWS/Azure).
Implement and manage data infrastructure components such as Delta Lake, Unity Catalog, and Databricks workflows to enable scalable data analytics.
4-8 years of professional experience in data engineering or related roles.
Strong coding skills in Python, PySpark, and SQL mandatory.
Experience with cloud platforms AWS and/or Azure mandatory.
B.Tech/BE, M.Tech, MBA, or MCA degree mandatory.
Proven hands-on experience specifically with Databricks platform components including Delta Lake, Delta Live Tables, Auto Loader, and Structured Streaming.
Familiarity with Spark performance tuning, Lakehouse architecture, and familiarity with orchestration tools like Airflow or Azure Data Factory.
Prior exposure to CI/CD, Git, Databricks SQL, MLflow, and optionally Databricks certification; healthcare domain experience preferred but not mandatory.