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Popular data-engineer role in Noida with common toolset and metro talent pool producing medium competition.
Platform-specific Databricks, Delta Lake and Kafka expertise moderately limits cross-industry transferability.
Mandatory PySpark, Databricks, Delta Lake and Kafka requirements with senior expectations create high shortlisting strictness.
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Design and implement scalable batch and streaming data pipelines using PySpark, Apache Kafka, Databricks Workflows, and Delta Lake.
Architect and optimize enterprise-scale data solutions following Lakehouse architecture principles and data engineering best practices.
Lead and mentor data engineering teams while ensuring data quality, governance, and operational reliability across data platforms.
Mandatory skills: PySpark, Apache Kafka, Databricks Workflows, Delta Lake on Databricks.
Experience with workflow orchestration tools such as Apache Airflow or Databricks Workflows is required.
Work Experience Required: Not explicitly mentioned in the JD.
Location: Noida, UP, India.
Strong expertise in building and optimizing both batch and streaming data architectures for enterprise-scale platforms.
Experienced in driving data quality, validation, governance, and operational visibility in data engineering solutions.
Ability to collaborate across teams and mentor junior members to uphold engineering standards and continuous improvement.