Data Engineer

We are looking for a skilled and detail-oriented Data Engineer to design, build, and maintain scalable data systems and pipelines that support business operations, analytics, and decision-making. The ideal candidate has strong problem-solving skills, experience working with large datasets, and the ability to collaborate with cross-functional teams including analysts, developers, and stakeholders.

The Data Engineer will be responsible for ensuring data availability, reliability, integrity, and efficiency across various platforms and systems.

• Design, develop, and maintain scalable data pipelines and ETL/ELT processes.
• Collect, process, and transform structured and unstructured data from multiple sources.
• Build and optimize databases, data warehouses, and data lake solutions.
• Ensure data quality, consistency, security, and governance standards are maintained.
• Monitor and troubleshoot data workflows and system performance issues.
• Collaborate with data analysts, software engineers, and business teams to support data needs.
• Develop and maintain documentation related to data architecture, processes, and workflows.
• Optimize data systems for performance, scalability, and reliability.
• Support reporting, analytics, and business intelligence initiatives.
• Implement automation and best practices in data engineering processes.
• Stay updated with emerging technologies and industry trends related to data engineering. 

1. Work Experience: Minimum 2–3 years of experience in Data Engineering or related roles.
2. Cloud Expertise: Strong technical experience with at least two major cloud platforms (e.g., AWS S3/Redshift, GCP BigQuery, Azure Synapse).
3. Programming Skills: Proficient in Python, Java, or Scala, with strong advanced SQL capabilities.
4. Data Stack: Hands-on experience with data orchestration tools (such as Airflow, Prefect, or Dagster) and data processing frameworks (such as Spark or Flink).
5. Data Modeling: Good understanding of Data Warehouse, Data Lake, and data modeling concepts (Star Schema, Snowflake Schema).

Preferred Qualifications:

On-Premises Experience: Experience managing traditional on-premises data infrastructure such as Hadoop, SQL Server, PostgreSQL, or Oracle.

DevOps / IaC: Familiar with Docker, Kubernetes, or Terraform.

Data Governance: Understanding of data security best practices and regulatory compliance standards (such as GDPR or Indonesia’s PDP Law).