Data Engineer: Scalable Pipelines & Data Platforms

JobCubby; Singapore; On-site; SGD 80,000 - 120,000; Full time

Job summary

Zensar is seeking a skilled Data Engineer to design, develop, and maintain scalable data pipelines and data solutions. You will work with stakeholders, data scientists, analysts, and application teams to enable efficient data ingestion, transformation, storage, and reporting.

The role emphasizes data quality, governance, and collaboration across cloud-based platforms, with an opportunity to contribute to data warehousing and real-time processing initiatives.

Qualifications

• Bachelor's or master's in CS/IT/Engineering or related field.
• Strong SQL and data modeling fundamentals are required.
• Hands-on experience with Python or Spark for data processing.
• Familiarity with cloud data platforms and data governance.

Responsibilities

• Design, build, and maintain scalable data pipelines and ETL/ELT processes.
• Develop and optimize data integration across structured and unstructured sources.
• Build and manage data warehouses, data lakes, and data marts.
• Ensure data quality, integrity, security, and governance.
• Create and maintain data models for reporting and analytics.
• Optimize processing performance and troubleshoot production issues.
• Collaborate with cross-functional teams to meet data requirements.
• Implement monitoring, logging, and alerting for data pipelines.
• Support cloud-based data platforms and migrations.
• Maintain documentation for data architecture and workflows.

Skills

SQL & DB concepts

ETL/ELT tools

Python

PySpark

Big data tech

Azure data platforms

RDBMS

Data warehousing

CI/CD & Git

Analytical skills

Education

Bachelor's or Master's in CS/IT/Engineering

Tools

Azure Data Factory

Azure Databricks

Azure Synapse

Job description

Zensar is seeking a skilled Data Engineer to design, develop, and maintain scalable data pipelines and data solutions. You will work with stakeholders, data scientists, analysts, and application teams to enable efficient data ingestion, transformation, storage, and reporting.

The role emphasizes data quality, governance, and collaboration across cloud-based platforms, with an opportunity to contribute to data warehousing and real-time processing initiatives.