Deskripsi pekerjaan Data Engineer - ETL - (Banking Project) PT Aktualisasi Gratia Talenta Indonesia
Job Summary:
We are seeking a skilled Data Engineer with at least 3 years of professional experience in designing, developing, and maintaining scalable data pipelines and data integration solutions. The ideal candidate has strong expertise in ETL development, real-time data streaming, database management, and big data technologies. Experience with MongoDB is mandatory, along with proficiency in Python and modern data engineering tools.
Key Responsibilities:
- Design, develop, and maintain scalable ETL/ELT pipelines for data ingestion, transformation, and loading.
- Build and optimize data integration processes using SSIS, Talend, Kettle (Pentaho Data Integration), or Pentaho.
- Develop and maintain real-time data streaming pipelines using Apache Kafka, Debezium, Apache Flink, and Apache Spark.
- Design and optimize data models for both relational and NoSQL databases.
- Develop and maintain high-performance SQL queries, stored procedures, and database objects.
- Manage and optimize databases including PostgreSQL, Oracle Database, MongoDB, SQL, NoSQL, GSQL, and TG.
- Ensure data quality, consistency, integrity, and security across data platforms.
- Monitor, troubleshoot, and optimize ETL jobs and streaming applications to ensure high availability and performance.
- Collaborate with Business Analysts, Data Analysts, Data Scientists, and Software Engineers to understand business requirements and deliver reliable data solutions.
- Implement data validation, monitoring, logging, and error-handling mechanisms.
- Support data migration, replication, and synchronization initiatives.
Requirements:
Bachelor's Degree in Computer Science, Information Technology, Engineering, or a related field.
Minimum 3 years of experience as a Data Engineer or in a similar role.
Strong experience with ETL development using SSIS, Talend, Kettle (Pentaho Data Integration), or Pentaho.
Hands-on experience with Debezium, Apache Kafka, Apache Flink, and Apache Spark.
Strong proficiency in Python for data processing, automation, and scripting.
Experience with relational databases including PostgreSQL and Oracle Database.
Strong SQL programming skills and experience with query optimization.
Hands-on experience with MongoDB (Mandatory).
Experience working with NoSQL, GSQL, and TG technologies.
Knowledge of data warehousing concepts, data modeling, and ETL best practices.
Familiarity with batch and real-time data processing architectures.
