Kerja Sepenuh Masa, Data AI Engineer di Basil Technologies Johor - Maukerja

We are looking for a Data Engineer to own the data pipelines, storage architecture, and AI-enablement layer for a media monitoring platform. This role will focus on building reliable data foundations for large-scale ingestion, processing, enrichment, and serving of multilingual media content for NLP and machine learning use cases.

Core Responsibilities

• Design and maintain scalable batch and streaming pipelines for news, social media, web, and broadcast data ingestion.
• Build ETL/ELT processes to clean, normalize, deduplicate, enrich, and structure unstructured media content.
• Prepare datasets, labels, and feature-ready data for AI/ML model training, fine-tuning, and evaluation.
• Support NLP workflows such as entity extraction, topic classification, sentiment analysis, clustering, summarisation, and alerting.
• Ensure data quality, schema consistency, lineage, observability, and fault tolerance across the platform.
• Optimize storage, compute, and query performance across the data stack.
• Implement governance, access control, and auditability for sensitive or regulated content.
• Work closely with the full stack developer to align backend data services with product requirements and API consumption patterns.

Required Skills

• Strong experience in data engineering, pipeline orchestration, and distributed data processing.
• Proficiency in Python and SQL.
• Experience with cloud data platforms, object storage, warehouses, workflow orchestration, and message queues.
• Familiarity with unstructured text data, NLP workflows, and ML data preparation.
• Understanding of data modeling, system reliability, monitoring, and performance tuning.

Preferred Experience

• Background in media monitoring, social listening, content intelligence, or news analytics.
• Experience with multilingual datasets and text-heavy pipelines.
• Exposure to LLM-based systems, vector search, or retrieval pipelines.
• Familiarity with secure deployment environments and data governance practices.