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.
