Data Engineer & AI - ETL - (Banking Project)

Deskripsi pekerjaan Data Engineer & AI - ETL - (Banking Project) PT Aktualisasi Gratia Talenta Indonesia

Job Description

Design, develop, and maintain data engineering solutions to support data generation, collection, integration, and processing across multiple systems.

Build, optimize, and maintain scalable and reliable data pipelines to support data analytics, AI, and business intelligence initiatives.

Develop and implement ETL (Extract, Transform, Load) processes to migrate, transform, and deploy data across different platforms and systems.

• Perform data integration from various internal and external sources while ensuring data accuracy, consistency, completeness, and quality.
• Monitor data pipeline performance, troubleshoot data processing issues, and implement improvements to enhance reliability and efficiency.

Collaborate with data scientists, AI engineers, business analysts, and other stakeholders to understand data requirements and deliver appropriate data solutions.

• Apply data engineering best practices, including data validation, error handling, documentation, and workflow automation.
• Support the development and maintenance of data infrastructure for AI and machine learning use cases.

Ensure data solutions comply with applicable data governance, security, privacy, and regulatory requirements, particularly in financial services environments.

Work closely with business and technical teams to translate business requirements into effective data engineering solutions.

Requirements

• Minimum Bachelor’s Degree (S1) in Computer Science, Information Technology, Data Science, Software Engineering, or a related field.
• 5–7 years of professional experience in data engineering, data development, or a closely related technical role.
• Experience in the banking or financial services industry is highly preferred.
• Experience working at a consulting firm or technology consulting company is an advantage.

Strong understanding of data engineering concepts, including data integration, data transformation, data processing, and data pipeline development.

• Hands-on experience developing and maintaining ETL/ELT processes and managing data migration across systems.
• Proficiency in SQL and experience working with relational databases and/or data warehouses.
• Experience with programming or scripting languages such as Python, Java, or Scala.
• Familiarity with data pipeline orchestration and workflow automation tools such as Apache Airflow or equivalent platforms.
• Understanding of data quality management, data validation, data governance, and data security principles.
• Familiarity with cloud-based data platforms and big data technologies is an advantage.
• Strong analytical and problem-solving skills, with the ability to troubleshoot complex data processing issues.

Preferred Candidate Profile

Candidates with relevant experience delivering data engineering solutions for banking, financial institutions, or other regulated financial services organizations.

Candidates with experience supporting AI, machine learning, analytics, or enterprise data platform initiatives.