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Known employer, mid-level data role, metro location, and common skillset increase candidate competition.
Domain-specific cloud and Databricks skills moderate transferability across industries.
Explicit 6+ years and mandatory PySpark/Databricks/Azure skills enforce strict shortlisting.
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Design, develop, and optimize ETL/ELT data pipelines using PySpark and Spark SQL in Azure Databricks environment.
Build and orchestrate data workflows integrating on-premise and cloud systems using Azure Data Factory, HVR/Fivetran, and secure networks.
Collaborate with cross-functional teams to ensure scalable, high-quality data solutions and support CI/CD automation and troubleshooting.
6+ years of hands-on experience in data engineering and data pipeline development.
Bachelor's degree in Computer Science, Engineering, or related field.
Proficiency in PySpark, Spark SQL, Azure cloud services (ADF, Databricks, ADLS), and SQL performance tuning.
Experience with Git, CI/CD pipelines, and hybrid data integration tools (ADF, HVR/Fivetran).
Experienced in building and optimizing scalable data pipelines in cloud-native Azure environments with Databricks expertise.
Skilled in hybrid data integration between on-premise and cloud sources with strong knowledge of orchestration and streaming tools like Airflow and Kafka.
Capable of collaborating with analysts, scientists, and business users to align data solutions with requirements and troubleshoot complex pipeline issues.