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Junior Data Engineer

Junior Data Engineer

Rapsys Technologies Pte. LtdKuala Lumpur, Kuala Lumpur, Malaysia
9 hours ago
Job description

Primary Objectives

  • Provide technical leadership, guidance, and act as a reference point for data engineering and analytical solutions, especially in Data Products.
  • Develop and implement modern Data Engineering solutions aligned with industry best practices.
  • Drive DataOps / MLOps knowledge-sharing and collaboration across business and IT teams.
  • Translate conceptual and logical data models into efficient and maintainable physical data implementations.

Key Responsibilities

  • Design and evolve the overall data architecture, ensuring scalability, flexibility, and compliance with enterprise standards.
  • Build efficient, secure, and reliable data pipelines using the Bronze-Silver-Gold architecture within EDL.
  • Develop and orchestrate scheduled jobs in the EDL environment to support continuous ingestion and transformation.
  • Implement Apache Iceberg for data versioning, governance, and optimization.
  • Leverage the Medallion framework to standardize data product maturity and delivery.
  • Govern metadata, data lineage, and business glossary using tools like Apache Atlas.
  • Ensure data security, privacy, and regulatory compliance across all data processes.
  • Support Data Mesh principles by collaborating with domain teams to design and implement reusable Data Products.
  • Integrate data across structured, semi-structured, and unstructured sources from enterprise systems such as ODS and CRM systems.
  • Drive adoption of DataOps / MLOps best practices and mentor peers across units.
  • Generate and manage large-scale batch files using Spark and Hive for high-volume data processing.
  • Design and implement document-based data models and transform relational models into NoSQL document-oriented structures (eg NoSQL Database or similar system).

    • Required Skills & Qualifications

  • Bachelor's, Master's, or PhD in Computer Science, Data Engineering, or a related discipline.
  • 3–6 years of experience in data engineering and distributed data systems.
  • Strong hands-on experience with Apache Hive, HBase, Kafka, Solr, Elasticsearch.
  • Proficient in data architecture, data modelling, and pipeline scheduling / orchestration.
  • Operational experience with Data Mesh, Data Product development, and hybrid cloud data platforms.
  • Familiarity with CRM systems, including CRM system, and data sourcing / mapping strategies.
  • Proficient in managing metadata, glossary, and lineage tools like Apache Atlas.
  • Proven experience in generating large-scale batch files using Spark and Hive.
  • Strong understanding of document-based data models and the transformation of relational schemas into document-oriented structures.

    • Additional Technical & Business Competencies

  • Expertise in data administration, modelling, mapping, collection, and distribution.
  • Strong understanding of business workflows to support metadata governance.
  • Hands-on experience with analytics and DWH tools (e.g., SAS, Oracle, MS SQL, Python, R Programming).
  • Familiarity with data modelling tools (e.g., ERWIN), and enterprise databases (Oracle, IBM DB2, MS SQL, Hadoop, Object Store).
  • Experience working across hybrid cloud environments (e.g., AWS, Azure Data Factory).
  • In-depth knowledge of ETL / ELT processes and automation frameworks.
  • Analytical thinker with strong problem-solving and communication skills.
  • Able to collaborate effectively across technical and business teams.
  • Proven ability to deliver high-quality outcomes within

    • Job Type : Contract

    Contract length : 12 months

    Pay : RM4, RM6,000.00 per month

    Work Location : In person

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    Data Engineer • Kuala Lumpur, Kuala Lumpur, Malaysia