Cloud Data Engineer — AWS Migration Specialist

PERSOL SINGAPORE PTE. LTD.; Singapore; On-site; SGD 90,000 - 150,000; Full time

Job summary

PERSOL SINGAPORE PTE. LTD.

is seeking a Data Engineer with 5+ years of experience to build scalable data platforms and modern pipelines, using Python, SQL, PySpark, Hadoop/Cloudera and AWS data services, including migrating enterprise workloads from Cloudera/Hadoop to AWS. You will design, develop, and optimize cloud-native data solutions that support analytics, reporting, and business-critical applications; lead migration efforts; ensure data quality, governance, and security; and collaborate

Qualifications

• 5+ years of experience in Data Engineering, Data Warehousing, or Big Data technologies.
• Strong programming in Python, SQL, and PySpark.
• Hands-on experience with Hadoop/Cloudera ecosystem (HDFS, Hive, Impala, Spark).
• Experience migrating workloads from Cloudera/Hadoop to AWS.

Responsibilities

• Design, develop, and maintain scalable ETL processes and data pipelines using Python, SQL, and PySpark.
• Lead migration of data workloads from Cloudera/Hadoop to AWS.
• Build and optimize cloud-native data solutions with AWS S3, Glue, EMR, Athena, and Redshift.
• Develop data ingestion, transformation, and integration frameworks for analytics.
• Monitor and improve pipeline performance, reliability, and security.
• Collaborate with architects, analysts, and engineers to translate requirements into solutions.

Skills

Python

SQL

PySpark

Hadoop/Cloudera

AWS data services

Data engineering

Tools

HDFS

Hive

Impala

Spark

CDP

Job description

PERSOL SINGAPORE PTE. LTD.

is seeking a Data Engineer with 5+ years of experience to build scalable data platforms and modern pipelines, using Python, SQL, PySpark, Hadoop/Cloudera and AWS data services, including migrating enterprise workloads from Cloudera/Hadoop to AWS. You will design, develop, and optimize cloud-native data solutions that support analytics, reporting, and business-critical applications; lead migration efforts; ensure data quality, governance, and security; and collaborate