Senior Cloudera Spark Developer
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We are seeking a highly experienced Senior Cloudera Spark Developer with a strong background in big data technologies. The ideal candidate will be responsible for designing, developing, and optimizing large-scale data processing solutions using Apache Spark within the Cloudera ecosystem. This role requires deep technical expertise in Spark, PySpark, Scala, and SQL, along with a proven track record of delivering robust and scalable data pipelines.
Key Responsibilities:
- Design, develop, and implement high-performance data processing applications using Apache Spark (PySpark and Scala).
- Optimize Spark jobs for efficiency, performance, and cost-effectiveness on the Cloudera platform.
- Develop and maintain complex SQL queries for data extraction, transformation, and analysis.
- Collaborate with data engineers, data scientists, and business stakeholders to understand data requirements and translate them into technical solutions.
- Build and manage data pipelines for batch and real-time data processing.
- Perform code reviews, testing, and debugging of Spark applications.
- Troubleshoot and resolve performance bottlenecks and issues in Spark environments.
- Stay up-to-date with the latest advancements in big data technologies, particularly within the Cloudera ecosystem.
- Mentor junior developers and contribute to best practices in data development.
Required Skills and Qualifications:
- 7+ years of experience in big data development, with a significant focus on Apache Spark.
- Proficiency in PySpark and Scala for developing Spark applications.
- Expertise in SQL for data manipulation and complex querying.
- Hands-on experience with the Cloudera ecosystem (e.g., HDFS, Hive, Impala, Spark on YARN).
- Strong understanding of distributed computing principles and data warehousing concepts.
- Experience with data modeling, ETL/ELT processes, and data pipeline orchestration.
- Excellent problem-solving and analytical skills.
- Strong communication and collaboration abilities.
Preferred Qualifications:
- Experience with cloud platforms (AWS, Azure, GCP) and their big data services.
- Familiarity with other big data tools and technologies (e.g., Kafka, Flink, NoSQL databases).
- Experience with CI/CD pipelines and DevOps practices for big data applications.
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