Job description for ETL Data Architect – Tencent Cloud at PT Digital Tech Asia
Position: ETL Data Architect
Location: Jakarta, Indonesia
Working Arrangement: Hybrid
Start Date: Immediate preferred
Contract Period : 6 Month (extendable)
Role Summary
Our client is looking for an ETL Data Architect to lead the design, transformation, and migration of large-scale legacy ETL jobs to Tencent Cloud and modern data platforms.
The role requires strong experience in analyzing legacy ETL source code, restoring business logic, designing migration and transformation patterns, and providing technical direction to ETL development teams.
Key Responsibilities
- Lead analysis and reverse engineering of legacy ETL jobs, including Graph, DML, XFR, SAP, and PL/source code.
- Analyze existing ETL logic and restore business/data transformation logic for migration.
- Design ETL migration architecture and transformation patterns for modern platforms.
- Lead and guide the migration of legacy ETL workloads to Tencent Cloud.
- Design and optimize high-throughput, scalable data pipelines.
- Review ETL development outputs and provide technical guidance to ETL Development Engineers.
- Perform performance tuning and optimization of data pipelines and ETL processes.
- Define technical standards, best practices, and reusable migration patterns.
- Drive end-to-end architecture for large-scale ETL and data migration projects.
- Collaborate with Data Engineers, Developers, Architects, and business stakeholders.
Mandatory Requirements
- Bachelor's degree or above in Computer Science, Information Technology, or a related field.
- 5+ years of hands-on experience in Legacy ETL projects.
- Experience with Tencent Cloud WeData / DLC.
- Experience with Apache Spark, Spark SQL, Airflow, or other modern data platforms.
- Experience in large-scale ETL migration / modernization projects.
- Background in telecommunications, data warehouse, or big data projects.
- Experience with data lake/lakehouse architecture.
- Experience working with high-volume enterprise data environments.
- Immediate joiner is highly preferred.

