Data Engineer (Hybrid)

Azura Labs Official; Jakarta Utara; On-site; IDR 279,000,000 - 424,080,000; Full time

Job summary

Azura Labs Official is seeking a Data Engineer to build and maintain reliable data pipelines, integrating data from multiple sources into data warehouses or data lakes while ensuring quality.

You will write efficient SQL, work with Python for data processing, and collaborate with Analysts, Data Scientists, and Eng teams. On-site role in Jakarta provides opportunities to optimize and monitor pipeline performance.

Qualifications

• 3–5 years of experience as a Data Engineer or in a similar role.
• Strong SQL skills and a solid understanding of basic data modeling.
• Hands-on experience using Python for data processing.
• Experience with ETL/ELT tools or workflow orchestration platforms such as Airflow, dbt, Dagster, or similar tools.
• Familiarity with data warehouses such as BigQuery, Snowflake, Redshift, or PostgreSQL.
• Understanding of data quality, partitioning, indexing, and pipeline monitoring.

Responsibilities

• Build and maintain reliable ETL/ELT pipelines.
• Process and integrate data from multiple sources into data warehouses or data lakes.
• Write efficient and maintainable SQL queries.
• Ensure data quality, consistency, and validity across data pipelines.
• Collaborate with Data Analysts, Data Scientists, Product, and Engineering teams.
• Monitor, troubleshoot, and optimize pipeline performance.

Skills

SQL

Python

ETL/ELT

Data Modeling

Data Warehouses

Airflow

dbt

Dagster

Spark

Kafka

Job description

This Data Engineer position is focused on building and maintaining reliable data pipelines, processing and integrating data from multiple sources into data warehouses or data lakes, and ensuring data quality and consistency across systems.

Key Responsibilities

Build and maintain reliable ETL/ELT pipelines

Process and integrate data from multiple sources into data warehouses or data lakes

Write efficient and maintainable SQL queries

Ensure data quality, consistency, and validity across data pipelines

Collaborate with Data Analysts, Data Scientists, Product, and Engineering teams

Monitor, troubleshoot, and optimize pipeline performance.

Requirements

3–5 years of experience as a Data Engineer or in a similar role

Strong SQL skills and a solid understanding of basic data modeling

Hands-on experience using Python for data processing

Experience with ETL/ELT tools or workflow orchestration platforms such as Airflow, dbt, Dagster, or similar tools

Familiarity with data warehouses such as BigQuery, Snowflake, Redshift, or PostgreSQL

Understanding of data quality, partitioning, indexing, and pipeline monitoring.

Nice to Have

Experience with cloud platforms such as GCP, AWS, or Azure

Familiarity with Apache Spark, Apache Kafka, or data streaming

Experience working with analytics teams or production data platforms.

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