Junior Data Engineer

Populix; Daerah Khusus Ibukota Jakarta; On-site; IDR 504.795.000 - 841.326.000; Full time

Job summary

A leading consumer insights platform in Jakarta is seeking a Junior Data Engineer to design and maintain scalable data pipelines. You will collaborate with senior engineers and product teams while utilizing modern cloud technologies like GCP or AWS to ensure reliable data infrastructure. Key responsibilities include ETL/ELT pipeline development, data quality checks, and SQL query writing. This role is ideal for someone early in their data engineering career looking to grow in a fast-paced environment.

Qualifications

• Familiarity with ETL/ELT processes.
• Understanding of data transformation tools.
• Experience with data workflow orchestration.

Responsibilities

• Design and maintain ETL/ELT data pipelines.
• Optimize data workflows on cloud platforms.
• Write efficient SQL queries for analytics.
• Collaborate closely with product teams.
• Implement data quality checks and monitoring.

Skills

Python

Apache Spark

Cloud platforms (GCP or AWS)

SQL

Data quality checks

Tools

BigQuery

Apache Airflow

DBT

Job description

About us

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.

About this job

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).

Job Description and Requirements

• 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.