Job Description
- Design, build, and maintain scalable data pipelines to support data integration, transformation, and analysis across multiple systems.
- Develop and manage ETL (Extract, Transform, Load) processes to ensure data accuracy, consistency, and availability for business intelligence and analytics.
- Work closely with cross-functional teams, including Data Analysts, Software Engineers, and Business Units, to understand data requirements and deliver reliable data solutions.
- Optimize database performance and ensure data quality, governance, and security standards are met.
- Create and maintain technical documentation, including data flow diagrams, architecture design, and process descriptions.
- Support continuous improvement by implementing automation and adopting new data technologies or best practices.
- For higher-level roles: provide technical leadership, mentor junior team members, and contribute to strategic planning of data architecture and analytics initiatives
Minimum Qualifications
- Minimum education: Diploma (D3) in any major, preferably in Information Technology, Computer Science, or related field.
- Experience in data engineering or software development aligned with the position level (Junior, Middle, or Senior).
- Proficiency in at least one programming language such as SQL, Java, Python, or PHP.
- Hands-on experience with ETL tools and data processing technologies such as ODI, Datastage, Talend, or Pentaho.
- Strong knowledge of relational and non-relational databases, including Oracle, MySQL, PostgreSQL, MS SQL, DB2, BigQuery, or Big Data ecosystems.
- Familiarity with data warehouse concepts, data modeling, and API/Web Service (SOAP/REST) integration.
- Understanding of ISO 8583 and financial/banking data flow is a strong advantage.
- Experience working in an Agile development environment and familiarity with Software Development Life Cycle (SDLC) best practices.
- Strong analytical and problem-solving skills with the ability to translate business requirements into technical data solutions.
- For senior levels: proven experience in leading data engineering initiatives, architecture design, and mentoring team members.
- Experience or interest in AI/Gen AI or data automation tools is a plus.