 
						Big Data Engineer
2 days ago
Job Title: Big Data Engineer (Java, Spark, Hadoop)Location : Singapore Experience : 7- 12 years Employment Type : Full-Time Open to Citizens and SPR only | No Visa sponsorship available Job Summary We are looking for a Senior Big Data Engineer with 7–12 years of experience to join our growing data engineering team. The ideal candidate will bring deep expertise in Java , Apache Spark , and Hadoop ecosystems, and have a strong track record of designing and building scalable, high-performance big data solutions. This role is critical to ensuring robust data processing and delivering clean, actionable data for business insights and advanced analytics. Key Responsibilities Design, build, and optimize large-scale, distributed data processing systems using Apache Spark , Hadoop , and Java . Lead the development and deployment of data ingestion , ETL/ELT pipelines , and data transformation frameworks . Work with cross-functional teams to gather data requirements and translate them into scalable data solutions. Ensure high performance and reliability of big data systems through performance tuning and best practices. Manage and monitor batch and real-time data pipelines from diverse sources including APIs, databases, and streaming platforms like Kafka . Apply deep knowledge of Java to build efficient, modular, and reusable codebases. Mentor junior engineers, participate in code reviews, and enforce engineering best practices. Collaborate with DevOps teams to build CI/CD pipelines and automate deployment processes. Ensure data governance , security , and compliance standards are maintained. Required Qualifications 7–12 years of experience in big data engineering or backend data systems. Strong hands-on programming skills in Java ; exposure to Scala or Python is a plus. Proven experience with Apache Spark , Hadoop (HDFS, YARN, MapReduce), and related tools. Solid understanding of distributed computing , data partitioning, and optimization techniques. Experience with data access and storage layers like Hive , HBase , or Impala . Familiarity with data ingestion tools like Apache Kafka , NiFi , Flume , or Sqoop . Comfortable working with SQL for querying large datasets. Good understanding of data architecture , data modeling , and data lifecycle management . Experience with cloud platforms like AWS , Azure , or Google Cloud Platform . Strong problem-solving, analytical, and communication skills. Preferred Qualifications Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field. Experience with streaming data frameworks such as Spark Streaming , Kafka Streams , or Flink . Knowledge of DevOps practices , CI/CD pipelines, and infrastructure as code (e.g., Terraform). Exposure to containerization (Docker)and orchestration (Kubernetes) . Certifications in Big Data technologies or Cloud platforms are a plus. Please note that this is an equal opportunities employer. #J-18808-Ljbffr
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