Data Quality Engineer

Krom; Jakarta Pusat; On-site; IDR 180,000,000 - 300,000,000; Full time

Job summary

Krom is seeking a detail-oriented Data Quality Engineer to ensure accuracy and reliability of data across systems. You will design and implement data quality frameworks, with a focus on dbt testing and documentation, collaborating with data engineers and analytics teams.

The role covers automated quality checks in ETL/ELT pipelines, defining data quality metrics, resolving issues, and contributing to governance initiatives.

Qualifications

• Bachelor's degree in a relevant field.
• Strong SQL skills and data pipeline experience.
• Familiar with cloud data platforms and dbt testing frameworks.
• Knowledge of data quality frameworks and tooling.
• Excellent analytical and communication skills.

Responsibilities

• Design, develop, and maintain data quality frameworks and validation rules.
• Implement automated data quality checks in ETL/ELT pipelines.
• Collaborate with data engineering and Analytics Team to integrate quality checks.
• Define and monitor data quality metrics (DQMs).
• Investigate and resolve data quality issues with relevant teams.
• Document data quality processes, dbt models, and best practices.
• Partner with stakeholders to define data quality requirements for new projects.

Skills

SQL

Analytical thinking

Communication

Collaboration

Attention to detail

Education

Bachelor's degree in Computer Science, Information Systems, Data Engineering, or related field

Tools

dbt

Great Expectations

Informatica DQ

Collibra

Job description

We are seeking a detail-oriented and proactive Data Quality Engineer to join our team. The role is responsible for ensuring the accuracy, completeness, consistency, and reliability of data across various systems and platforms. The Data Quality Engineer will collaborate with data engineers, analytics, and business stakeholders to design and implement processes, tools, and frameworks—particularly leveraging dbt and other modern data quality tools—to improve and maintain high-quality data for decision-making and business operations.

Key Responsibilities:

• Design, develop, and maintain data quality frameworks and validation rules, with a strong focus on dbt testing and dbt documentation.
• Implement automated data quality checks within ETL/ELT pipelines (e.g., dbt tests, Great Expectations).
• Collaborate with data engineering and Analytics Team to integrate quality checks into data workflows.
• Define and monitor data quality metrics (DQMs), such as completeness, validity, uniqueness, and timeliness.
• Investigate and resolve data quality issues by identifying root causes and working with relevant teams.
• Document data quality processes, dbt models, and best practices.
• Partner with stakeholders to define data quality requirements for new projects and integrations.
• Support regulatory, compliance, and governance initiatives by maintaining high standards of data integrity.

About You:

• Bachelor’s degree in Computer Science, Information Systems, Data Engineering, or related field.
• Strong SQL skills and hands‑on experience with databases, dbt, ETL/ELT tools, and data pipelines.
• Familiarity with cloud data platforms (e.g., BigQuery).
• Experience with dbt testing frameworks (e.g., schema tests, custom tests, data documentation).
• Knowledge of data quality frameworks, profiling tools, or data catalog solutions (e.g., Great Expectations, Informatica DQ, Collibra).
• Strong analytical and problem‑solving skills with keen attention to detail.
• Good understanding of data governance, master data management, and regulatory compliance.
• Excellent communication skills and ability to work with cross‑functional teams.

Nice to Have:

• Experience with Python for custom dbt tests or validation scripts.
• Exposure to streaming data pipelines (Kafka, Pub/Sub).