Data Engineer: Build Scalable Pipelines & Insights

E-Outsource Asia

Kampung Malaysia Tambahan

On-site

MYR 90,000 - 150,000

Full time

16 hours ago

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Job summary

E-Outsource Asia is hiring a Data Engineer to design, develop, and maintain scalable data pipelines and enterprise data platforms. You will collaborate with stakeholders, solution architects, and data teams to ensure high-quality, governable data across the organization.

The role requires 3–8 years of data engineering experience, strong SQL and programming skills (Python/Scala), and hands-on cloud experience (AWS/Azure/GCP). Experience with SAP/Salesforce and data governance is a plus.

Qualifications

Bachelor's degree in CS/IT/SE/Data Science or related field.
3-8 years of data engineering or data integration experience.
Strong knowledge of data warehousing and data lakes.
Experience with ETL/ELT tools and data integration platforms.
Proficiency in SQL and programming with Python or Scala.
Hands-on experience with AWS, Azure, or Google Cloud.
Experience integrating SAP, Salesforce, CRM/ERP systems.
Knowledge of data modeling concepts, including dimensional and relational modeling.
Familiarity with data governance and data quality practices.
Strong analytical and problem-solving skills.
Excellent communication and stakeholder management.

Responsibilities

Design, develop, and maintain end-to-end data pipelines for structured and unstructured data.
Build and support data integration between enterprise systems including SAP, Salesforce, CRM platforms.
Develop and optimize ETL/ELT processes to improve data quality, performance, and reliability.
Implement data models and transformation logic in alignment with enterprise data architecture standards.
Ensure data integrity, accuracy, and consistency across source and target systems.
Collaborate with Data Architects, Business Analysts, and Solution Architects in designing scalable data solutions.
Support analytics, dashboards, and AI/ML initiatives by providing trusted datasets.
Monitor and troubleshoot data pipelines, integration jobs, and platform performance issues.
Implement data governance, security, privacy, and compliance requirements within data solutions.
Maintain technical documentation, data dictionaries, and data lineage artifacts.
Identify opportunities for automation and continuous improvement in data engineering processes.