Lead Data

2 weeks ago


Jakarta, Jakarta, Indonesia Alphalitical Full time

Job Requirements:

  • Bachelor's or Master's degree in Computer Science, Data Engineering, AI/ML, or related field.
  • 3+ years experience as a Python Engineer, ideally with hands-on work in data crawling and structured data transformation for social insights.
  • 3+ years experience as an AI Engineer, including experience developing and training machine learning models using any major AI/ML frameworks (TensorFlow, PyTorch, etc.).
  • 3+ years in MLOps, with practical implementation of CI/CD for ML pipelines, containerization (Docker), orchestration (Kubernetes, Airflow), and deployment strategies.
  • Demonstrated ability to design cost-aware architectures, understanding cloud resource pricing models (AWS, GCP, Azure).
  • Strong understanding of Data Lake architectures, including batch and streaming data, with tools such as Spark, Kafka, Snowflake, Redshift, BigQuery, or similar.
  • Experience with cloud platforms (AWS/GCP/Azure) and their data ecosystems.
  • Familiarity with NLP techniques and tools for sentiment analysis.
  • Exposure to real-time data processing and stream analytics.
  • Strong documentation and system design skills.

Job Descriptions:

  • Lead the end-to-end design and development of data pipelines and infrastructure for large-scale data ingestion and processing.
  • Develop robust data crawling systems and structure data to power social listening tools.
  • Collaborate with Data Scientists to build AI/ML models focused on sentiment analysis of phrases and contextual language.
  • Implement and maintain MLOps practices for model training, versioning, monitoring, and deployment.
  • Architect and manage scalable Data Lake solutions using modern databases and big data technologies.
  • Estimate and monitor unit cost per tool/service, optimizing system architecture for performance and budget.
  • Produce comprehensive system flow documentation covering data pipelines, AI/ML integration, and storage design.
  • Collaborate cross-functionally with product, engineering, and analytics teams to align with business goals.


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