Big Data Engineer (PySpark)
Singapore, 02, SG
Capgemini
A global leader in consulting, technology services and digital transformation, we offer an array of integrated services combining technology with deep sector expertise.Roles and Responsibilities:
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Develop Spark Scala and PySpark jobs for data transformation and aggregation.
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Create unit tests for Spark transformations and helper methods.
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Utilize Spark and Spark SQL to read parquet data and create tables in Hive using the Scala API.
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Collaborate closely with the Business Analysts team to review test results and obtain sign-off.
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Prepare design and operations documentation for future reference.
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Conduct peer code quality reviews and act as a gatekeeper for quality checks.
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Engage in hands-on coding, often in a pair programming environment.
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Work within highly collaborative teams to build high-quality code.
Qualifications and Requirements:
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4-10 years of experience as a Hadoop data engineer.
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Strong expertise in Hadoop, Spark, Scala, PySpark, Python, Hive, and Impala.
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Familiarity with Oracle, Spark streaming, Kafka, and machine learning (ML).
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Proficiency in Agile methodologies, CI/CD, Git, Jenkins, and Cloudera Distribution.
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Solid understanding of data structures, data manipulation, distributed processing, application development, and automation.
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Experience in Core Banking or Finance domains is desirable.
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Cloud experience with AWS is a plus.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Agile APIs AWS Banking Big Data CI/CD Finance Git Hadoop Jenkins Kafka Machine Learning Oracle Parquet PySpark Python Scala Spark SQL Streaming
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