Big Data Engineer

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 Engineerwith 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.

To apply, email to [Confidential Information] / [HIDDEN TEXT] with the following details - Current CTC, Expected CTC, Notice period and Residential Status.