Data Engineer (Spark, Hadoop, Scala, Python - 2024 / 2025 pass out)
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The role
Design, develop, and maintain large-scale ETL pipelines using Hadoop, Spark, Hive, and Kafka to meet high-volume, low-latency data requirements.
Implement scalable, secure, and timely data processing solutions, and support production systems in a fast-paced environment.
Collaborate with engineers and product managers to translate requirements into robust data workflows and dashboards.
Contribute to design discussions, write code in Scala, Python, or Java, and perform testing to ensure data quality.
Leverage scheduling and orchestration tools (Airflow, Control-M) and version control (Git) for reliable deployments.
Demonstrate a proactive learning mindset, quickly acquiring new skills and adapting to changing business needs.
Implement scalable, secure, and timely data processing solutions, and support production systems in a fast-paced environment.
Collaborate with engineers and product managers to translate requirements into robust data workflows and dashboards.
Contribute to design discussions, write code in Scala, Python, or Java, and perform testing to ensure data quality.
Leverage scheduling and orchestration tools (Airflow, Control-M) and version control (Git) for reliable deployments.
Demonstrate a proactive learning mindset, quickly acquiring new skills and adapting to changing business needs.
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