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Remote role, metro location, and common data-engineer profile increase applicant competition.
Specialized Databricks and Azure skills moderately limit cross-industry transferability.
Explicit 6+ years and mandatory Databricks, PySpark, Delta Lake and Azure skills make filters strict.
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Design, build, and maintain scalable data pipelines and analytics solutions on Azure Databricks.
Implement and optimize ETL/ELT workflows using PySpark, Spark SQL, and Python focusing on performance, cost, and scalability.
Collaborate with stakeholders to support analytics and ML use cases while ensuring data quality, governance, security, and monitoring.
6+ years of experience in Data Engineering.
Proven hands-on expertise with Azure Databricks, Python, SQL, and Apache Spark/PySpark.
Experience working with Delta Lake and Azure Data Lake Storage Gen2.
Familiarity with Git version control and Azure Data Factory.
Experienced in managing large-scale distributed data processing and modern data engineering practices on Azure.
Skilled in performance tuning of Spark jobs and applying best practices in security and governance in cloud environments.
Comfortable integrating data engineering workflows with analytics, ML use cases, and exposure to CI/CD pipelines and streaming data technologies.