Junior Data Engineer

Kuala Lumpur
Tetap
Sepenuh masa

1 hari lepas

🌟 We're Hiring: Junior Data Engineer! 🌟We are seeking a motivated Junior Data Engineer to join our growing data team. The ideal candidate will have hands-on experience in building and maintaining data pipelines, working with databases, and supporting data-driven decision making across the organization.📍 Location: Kuala Lumpur, Malaysia
⏰ Work Mode: Work From Office
💼 Role: Junior Data EngineerWhat You'll Do:
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

Rapsys Technologies

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