Data Quality Engineer Intern
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About DANA
DANA is a leading Indonesian digital wallet platform committed to making every transaction simple, secure, and accessible. As a homegrown fintech company, we serve millions across Indonesia with cashless solutions—from payments and transfers to investments. We aim to build a trusted and inclusive financial ecosystem, driven by innovation, collaboration, and continuous learning.
Join us and be part of Indonesia’s digital transformation journey!
📌 What We’re Looking For: Data Quality Engineer Intern
You will assist in maintaining data quality and supporting data warehouse operations by performing data validation, monitoring data pipelines, helping identify and resolve data inconsistencies, and building data quality pipeline.
Responsibilities
Support the Data Team in gathering and preparing high-quality data for business needs
Perform data cleaning and preprocessing to ensure accuracy and consistency
Assist in implementing and maintaining data quality checks across datasets
Build and maintain Data Quality (DQ) pipelines
Monitor Data Warehouse performance with attention to cost efficiency and optimization
Ensure reliability and scalability of data pipelines and systems
Conduct research on AI-driven data quality and automation solutions
Stay updated on data engineering tools and continuously improve data processes
Collaborate with cross-functional teams to enhance data quality and governance
Requirements
Currently pursuing a Bachelor’s degree (final year/last semester) or a fresh graduate in Computer Science, Information Technology, or a related field from a reputable university (GPA ≥ 3.00)
Proficiency in programming languages such as Python and Bash/Shell
Strong knowledge of SQL, including:
Advanced querying (e.g., window functions)
Performance tuning and optimization
Understanding of Data Warehouse (DWH) Engineering concepts, including data modeling (e.g., star schema, slowly changing dimensions) and ETL/ELT pipeline development
Experience or familiarity with data pipeline orchestration tools such as Apache Airflow and Cron jobs
Familiarity with CI/CD pipelines and deployment practices
Working knowledge of Linux/Unix command-line environments
Exposure to containerization technologies (e.g., Docker, Kubernetes) is a plus
Awareness or experience in data quality tooling and observability and monitoring practices in data systems
Familiarity with AI/automation tools or workflow automation platforms (e.g., OpenCode, Claude Code) is an advantage
Strong analytical, problem-solving, and critical-thinking skills
Detail-oriented with a high commitment to data accuracy and reliability
Effective communication and teamwork skills
Self-motivated, proactive, and able to work independently
Eagerness to learn, adapt, and work with new technologies in a fast-paced environment