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Job Description & How to Apply Below
About the Role
The AI/ML Data Engineer will be a key player in our data and engineering teams, responsible for building and maintaining the robust data infrastructure that powers our machine learning models and data-driven products. This role is a critical bridge between data science and engineering, focusing on designing, constructing, and optimizing scalable data pipelines. The ideal candidate will ensure that data is clean, accessible, and ready for use by our data scientists and ML engineers, enabling them to build, train, and deploy models efficiently.
Hybrid based in Jakarta or Bandung, Indonesia
Key Responsibilities- Architect, construct, and manage data pipelines (ETL/ELT) that ingest, process, and transform large datasets from various sources into our data warehouse or data lake.
- Optimize our data infrastructure, including data warehouses, data lakes, and streaming platforms, to ensure high performance, scalability, and cost-effectiveness.
- Implement data validation, monitoring, and quality checks to maintain high data integrity. Develop and enforce data governance policies to ensure compliance and security.
- Work closely with software developers to understand data needs, deliver technical solutions, and facilitate a smooth data workflow.
- Bachelor’s degree in Computer Science, information Technology, or a related technical field.
- Minimum 3 years of experience in a Data Engineer or similar role.
- Strong proficiency in Python and experience with big data technologies such as Apache Spark.
- Demonstrated experience with a major cloud platform (e.g., AWS, GCP, or Azure), including their data-related services (e.g., S3, Big Query, Snowflake, Redshift).
- Solid understanding of data modeling, database systems (SQL and No
SQL), and data warehousing concepts. - Experience with containerization (Docker) and orchestration tools (e.g., Kubernetes) for deploying and managing data-intensive applications.
- Knowledge of MLOps principles and experience in building CI/CD pipelines for machine learning models.
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