• 8+ years of hands-on experience working with large-scale data systems in production environments.
• Proven experience designing, deploying, and integrating big data frameworks - PySpark, Kafka, Databricks. 
• Strong expertise in Python and SQL, with experience building and optimizing batch and streaming data pipelines.
• Experience with AWS cloud services and Linux-based environments.
• Background in building ETL/ELT pipelines and orchestrating workflows end-to-end.
  Proven experience designing, deploying, and operating data infrastructure / data platforms.
• Mandatory hands-on experience with Apache Spark in production environments. 
• Mandatory experience running Spark on Kubernetes.
• Mandatory hands-on experience with Apache Kafka, including Kafka connectors.
• Understanding of event-driven and domain-driven design principles in modern data architectures.
• Familiarity with infrastructure-as-code tools (e.g., Terraform) — advantage.
• Experience supporting machine learning or algorithmic applications — advantage.
• BSc or higher in Computer Science, Engineering, Mathematics, or another quantitative field.

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