Spark Developer (With Java)
Capgemini
We are seeking a highly skilled
Spark Developer with strong Java expertise
to design, develop, and optimize large-scale data processing applications. The ideal candidate will have hands‑on experience with
Apache Spark, Core Java, distributed computing, and big data technologies. The candidate will work closely with data engineers, architects, and business stakeholders to build scalable and high‑performance data solutions.
Key Responsibilities
Design, develop, and maintain scalable data processing applications using
Apache Spark and Java .
Develop batch and near real‑time data pipelines for large datasets.
Optimize Spark jobs for performance, memory management, and resource utilization.
Write efficient and reusable code using Java 8/11 features.
Work with distributed data processing frameworks and big data ecosystems.
Collaborate with cross‑functional teams to gather requirements and deliver data solutions.
Troubleshoot production issues and provide performance tuning recommendations.
Implement best practices for coding, testing, deployment, and monitoring.
Participate in code reviews and technical design discussions.
Ensure data quality, reliability, and scalability of applications.
Required Skills
Strong programming experience in
Core Java (Java 8 or above) .
Hands‑on experience with
Apache Spark (Spark Core, Spark SQL, DataFrames, Dataset APIs) .
Good understanding of
distributed computing concepts .
Experience with
HDFS, Hive, Hadoop Ecosystem .
Strong SQL skills and experience with relational databases.
Experience with data ingestion and transformation frameworks.
Familiarity with Linux/Unix environments.
Knowledge of REST APIs and microservices architecture.
Experience with Git and CI/CD processes.
Preferred Skills
Experience with
Spark Streaming, Kafka, Scala, or PySpark .
Exposure to cloud platforms such as
AWS, Azure, or GCP .
Experience with Airflow, Oozie, or similar workflow orchestration tools.
Understanding of Delta Lake, Iceberg, or Data Lake architectures.
Knowledge of containerization tools such as Docker and Kubernetes.
Qualifications
Bachelor's or Master's degree in Computer Science, Information Technology, or related field.
4+ years of software development experience.
2+ years of hands‑on experience developing applications using Apache Spark and Java.
#J-18808-Ljbffr
Spark Developer with strong Java expertise
to design, develop, and optimize large-scale data processing applications. The ideal candidate will have hands‑on experience with
Apache Spark, Core Java, distributed computing, and big data technologies. The candidate will work closely with data engineers, architects, and business stakeholders to build scalable and high‑performance data solutions.
Key Responsibilities
Design, develop, and maintain scalable data processing applications using
Apache Spark and Java .
Develop batch and near real‑time data pipelines for large datasets.
Optimize Spark jobs for performance, memory management, and resource utilization.
Write efficient and reusable code using Java 8/11 features.
Work with distributed data processing frameworks and big data ecosystems.
Collaborate with cross‑functional teams to gather requirements and deliver data solutions.
Troubleshoot production issues and provide performance tuning recommendations.
Implement best practices for coding, testing, deployment, and monitoring.
Participate in code reviews and technical design discussions.
Ensure data quality, reliability, and scalability of applications.
Required Skills
Strong programming experience in
Core Java (Java 8 or above) .
Hands‑on experience with
Apache Spark (Spark Core, Spark SQL, DataFrames, Dataset APIs) .
Good understanding of
distributed computing concepts .
Experience with
HDFS, Hive, Hadoop Ecosystem .
Strong SQL skills and experience with relational databases.
Experience with data ingestion and transformation frameworks.
Familiarity with Linux/Unix environments.
Knowledge of REST APIs and microservices architecture.
Experience with Git and CI/CD processes.
Preferred Skills
Experience with
Spark Streaming, Kafka, Scala, or PySpark .
Exposure to cloud platforms such as
AWS, Azure, or GCP .
Experience with Airflow, Oozie, or similar workflow orchestration tools.
Understanding of Delta Lake, Iceberg, or Data Lake architectures.
Knowledge of containerization tools such as Docker and Kubernetes.
Qualifications
Bachelor's or Master's degree in Computer Science, Information Technology, or related field.
4+ years of software development experience.
2+ years of hands‑on experience developing applications using Apache Spark and Java.
#J-18808-Ljbffr
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