Data Engineer

Responsibilities 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.

Requirements 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.