Data Engineer - Apache Spark, Iceberg & Kafka (Thrissur)

This is a 12 weeks duration engagement. overlap work with US time zone

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\nWe are looking for experienced Data Engineers with 5+ years of experience, to join a 12-week engagement focused on building and supporting modern data engineering solutions. The ideal candidates should have strong hands-on experience across a broad range of data engineering technologies and be able to contribute with minimal ramp-up time.

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\nKey Responsibilities

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• Design, develop, and maintain scalable data engineering pipelines.

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• Work with large-scale data processing and streaming technologies.

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• Develop and optimize data pipelines using Apache Spark, Kafka, Airflow, and related technologies.

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• Work with modern data lake and data warehouse technologies, including Apache Iceberg and Snowflake.

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• Develop solutions using AWS cloud services.

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• Write efficient and maintainable code using Java, Python, and SQL.

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• Design and implement data models, including Star Schema designs.

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• Troubleshoot, optimize, and improve data processing workflows and pipeline performance.

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• Collaborate with technical teams to deliver data engineering solutions within defined timelines.

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\nRequired Skills & Experience

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• 5+ years of professional experience in Data Engineering

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• Strong hands-on experience with Apache Spark

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• Experience with Apache Iceberg

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• Experience with Apache Kafka

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• Experience with Apache Airflow

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• Experience with Snowflake

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• Strong experience with AWS

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• Proficiency in Java, Python, and SQL

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• Strong understanding of Data Modeling and Star Schema Design

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• Experience with Apache Flink is preferred

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\nCandidates with hands-on experience across the majority of the required technology stack are strongly preferred. Candidates should be able to contribute independently with limited onboarding or ramp-up time. There may be some flexibility around Apache Flink experience for candidates who demonstrate strong expertise across the other core technologies. Candidates with strong experience across up-to-date data engineering, cloud, streaming, and data platform technologies are encouraged to apply. .