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.
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