Data Engineer

Nodewave; Jakarta Utara; On-site; IDR 167,400,000 - 279,000,000; Full time

Job summary

Nodewave is seeking a Data Engineer to transform complex datasets into actionable insights across HR, Finance, and Operations. You will craft ETL pipelines, build data warehouses and data lakes, and collaborate with AI engineers to enable predictive analytics and dashboards.

Responsibilities include data quality checks, secure data access, and continuous infrastructure improvement. You will work with SQL, Python/Scala/Java, and modern tools like Airflow and dbt across structured and unstructured

Qualifications

• Proficient in SQL and at least one programming language (Python, Scala, or Java).
• Strong data modeling, ETL design, and batch/streaming data processing skills.
• Hands-on experience with modern data pipeline tools like Airflow and dbt.
• Experience with relational and non-relational databases (PostgreSQL, MySQL, MongoDB, S3).
• Experience handling large datasets and optimizing query performance.
• Collaborates with data scientists, analysts, and backend engineers.

Responsibilities

• Design and maintain scalable ETL pipelines from multiple sources.
• Build and optimize data warehouses, data lakes, and data marts.
• Collaborate with data scientists and AI engineers to ensure clean data.
• Implement data quality checks, monitoring, and logging.
• Automate data workflows using Airflow, dbt, or Python scripts.
• Work with structured and non-structured data sources.
• Ensure secure, governed access to datasets and APIs.
• Continuously improve data infrastructure based on usage and business needs.

Skills

SQL

Python

Scala

Java

Data modeling

ETL design

Batch processing

Streaming data

Big data handling

Query optimization

Cross-functional collaboration

Tools

Airflow

dbt

PostgreSQL

MySQL

MongoDB

S3

Job description

As a Data Engineer, you will transform complex datasets into meaningful insights to drive data-driven decisions across HR, Finance, and Operations. You’ll work closely with AI Engineers, Data Scientist, and stakeholders to develop models, dashboards, and predictive analytics systems. Core Responsibilities:

Design and maintain scalable ETL pipelines to process structured and unstructured data from multiple sources.

Build and optimize data warehouses, data lakes, and data marts to support downstream analytics and AI systems.

Collaborate closely with data scientists and AI engineers to ensure clean, accessible, and reliable data.

Implement data quality checks, monitoring, and logging to ensure data integrity and lineage.

Automate data workflows using tools like Airflow, dbt, or custom Python scripts.

Work with both structured (MySQL, PostgreSQL) and non-structured (pdf, images, ppt and many more) data sources.

Ensure secure, efficient, and governed access to enterprise-grade datasets and APIs.

Continuously improve data infrastructure based on usage feedback, scalability needs, and business goals.

Requirements

Must-Have Skills

Proficient in SQL and one programming language (Python, Scala, or Java)

Solid understanding of data modeling, ETL design, and batch/streaming data processing

Hands-on experience with modern data pipeline tools (e.g., Apache Airflow, dbt, or similar)

Familiar with both relational (PostgreSQL, MySQL) and non-relational (MongoDB, S3, etc.) databases

Experience working with large datasets and optimizing performance for data queries and storage

Comfortable collaborating with data scientists, analysts, and backend engineers