Data Engineer - Data Lake

Unison Group; Singapore; On-site; SGD 90,000 - 130,000; Full time

Job summary

Unison Group seeks a data engineer to design and deliver scalable data pipelines within a robust Data Lake platform on Hadoop/Spark ecosystems. You will champion ingestion, transformation, and governance across structured, semi-structured, and streaming data for enterprise analytics.

You will work with Java, Python, SQL, Spark, and CI/CD tools to ensure reliable, high-performance data processing and deployment automation. Strong collaboration with platform teams is expected.

Qualifications

• Strong experience designing and building scalable data pipelines in a data lake/enterprise data platform.
• Proficient in Java, Python, SQL, and Spark for batch and streaming data processing.
• Hands-on with Hadoop ecosystem components (HDFS, Hive, Impala) and data governance basics.

Responsibilities

• Design, develop, and maintain scalable data pipelines using Cloudera CDP/Hadoop stack.
• Develop high-performance batch and near real-time ingestion frameworks.
• Implement data ingestion mappings and transformations with Spark and HiveQL.

Skills

Java

Python

SQL

Spark

Hadoop

Unix/Linux

Shell scripting

Tools

Hadoop

Hive

Spark

Kafka

Oozie

Git

Jenkins

Azure DevOps

Job description

Develop and deliver scalable transformation frameworks across Hadoop platforms by building robust data pipelines, ingestion frameworks, and automation capabilities. Ensure efficient data processing, performance optimization, and reliable integration of enterprise data sources, while supporting data warehouse, enterprise analytics and downstream consumption requirements. This role offers an opportunity to work on large-scale data platforms handling structured, semi-structured, and streaming data across critical banking domains.

Data Engineering & Integration

• Design, develop, and maintain scalable data pipelines within the Enterprise Data Lake platform using Cloudera CDP, Hadoop, Spark, Hive, Java, Python, and SQL.
• Develop high-performance batch and near real-time data ingestion frameworks for onboarding enterprise source systems into the Data Lake.
• Develop complex transformation logic using Spark, HiveQL, SQL, and Java-based processing frameworks.
• Design and implement data ingestion patterns supporting structured, semi-structured, and unstructured datasets.
• Build and maintain batch and near real-time data integration solutions.
• Implement source-to-target mappings and ingestion specifications.

Hadoop & Cloudera Platform Development

• Develop and support solutions within the Cloudera Data Platform ecosystem.
• Build and maintain data pipelines leveraging:
  • Hadoop HDFS
  • Hive
  • Impala
  • Spark
  • Kafka
  • YARN, Oozie
• Perform deployment, troubleshooting, and performance tuning of applications running on the Hadoop ecosystem.
• Partner with platform teams to ensure optimal cluster utilization and workload management.

Data Quality & Governance

• Ensure adherence to Data Lake onboarding standards and governance requirements.
• Investigate and resolve data quality issues and production incidents.
• Ensure compliance with enterprise data governance standards.

DevOps & Platform Automation

• Integrate data engineering solutions into CI/CD pipelines using Git, Jenkins, Azure DevOps, or equivalent tools.
• Automate deployment, testing, monitoring, and operational support activities.
• Develop reusable frameworks and utilities to improve engineering productivity and platform scalability.

Production Support & Incident Management

• Provide L3 support for Data Lake application.
• Perform root cause analysis for production incidents and implement permanent fixes.
• Monitor pipeline execution, cluster health, and workload performance.
• Participate in release implementation, deployment validation, and post-production support activities.
• Strong hands on experience with Hadoop ecosystem and data pipeline orchestration.
• Hadoop/HDFS
• Hive
• Spark
• Unix/Linux scripting
• Shell scripting
• ETL/ELT development experience.
• Data modelling fundamentals.
• Performance tuning and optimization.
• Experience in Data Warehousing and Data Lake environments.
• Strong Java / Python competency with experiences.
• Strong SQL development skills.