Data Engineer jobs in Indonesia

Populix is a consumer insights platform that helps businesses connect with its database of respondents and provides them with insights to understand the preferences of Indonesian consumers better. Populix has a pool of over 1,000,000 diverse, readily accessible, and highly-qualified respondents across Indonesia. Its products range from intensive research studies to simple surveys and can be arranged on a project or subscription basis. Focusing on Indonesian consumers being super sticky to their phones, Populix facilitates a diverse range of data collection methods via its mobile app.

We are looking for a Junior Data Engineer to join our growing AI team. In this role, you will help design, build, and maintain scalable data pipelines that power analytics and data-driven decision-making across the organization. You will work closely with senior engineers, data analysts, and product teams to ensure high-quality, reliable data infrastructure using modern cloud technologies.

This is an excellent opportunity for someone early in their data engineering career who is eager to learn and grow in a fast-paced environment with hands‑on exposure to Python, Apache Spark, and cloud platforms (GCP or AWS).

• Design, develop, and maintain scalable ETL/ELT data pipelines using Python/PySpark/Rust to process structured and unstructured data.
• Build and optimize data workflows on cloud platforms (Google Cloud Platform or AWS), leveraging services such as BigQuery, Dataproc, Cloud Storage, S3, Glue, or EMR.
• Write efficient, well‑tested SQL queries to transform and aggregate data for analytics, reporting, and downstream consumption (Familiarity with transformation tools like DBT is a plus).
• Collaborate with data analysts, data scientists, and product teams to understand data requirements and deliver reliable data solutions.
• Implement data quality checks, monitoring, and alerting to ensure accuracy, completeness, and timeliness of data.
• Support and improve workflow orchestration using tools such as Apache Airflow, Dagster, Prefect, or similar schedulers.
• Assist in maintaining data warehouse and data lake architectures following best practices (e.g., Medallion Architecture, Star Schema).
• Participate in code reviews, documentation, and knowledge sharing within the engineering team.
• Troubleshoot and resolve data pipeline failures and performance issues in a timely manner.

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