Staff Data Engineer

M-DAQ Indonesia Technologies (Wallex) is a subsidiary of M-DAQ Global . We are not only allow you to make cross-border payments at better rates and faster speeds, we also provide you with the ability to convert and hold balances in multiple currencies so that you can properly plan, manage and hedge your currency needs all from one platform.

M-DAQ Global

is a pioneering fintech group specialising in foreign exchange (FX) & payment solutions that facilitate seamless cross-border transactions for businesses worldwide. Our proprietary technology empowers both large enterprises and SMEs to navigate international trade with FX clarity, certainty, and payment mobility. Headquartered in Singapore with an expanding presence across 7 countries and territories, M-DAQ Global provides a comprehensive suite of FX, collections, and payment solutions, as well as value-added services such as AI-driven KYB onboarding and enhanced risk management solutions, enabling businesses to transact across borders with ease amidst evolving needs. For more information, please visit: www.m-daq.com.

Role Overview The Staff Data Engineer is responsible for designing, building, and maintaining scalable and reliable data infrastructure that supports core business operations, analytics, and compliance requirements within the payments domain. This role plays a critical part in ensuring data availability, performance, and integrity across systems, while enabling data-driven decision-making and regulatory readiness.

Key Responsibilities Design, develop, and maintain scalable data pipelines and ETL/ELT processes to ingest, process, and transform data from multiple sources, including payment systems, banking partners, and third-party APIs. Build and maintain robust data architectures, including data warehouses, data lakes, and databases, ensuring accurate representation of business logic and efficient data access. Optimize database and query performance through tuning, indexing strategies, and schema design for both operational and analytical workloads. Establish and enforce data quality standards by implementing validation rules, monitoring frameworks, and automated testing. Implement data governance, security, and access controls to ensure compliance with regulatory requirements and protection of sensitive payment and customer data. Monitor, troubleshoot, and improve data pipelines to ensure reliability, scalability, and system performance. Develop and maintain data integration solutions to enable seamless data exchange between internal systems and external partners. Collaborate closely with product, engineering, risk, and compliance teams to understand data requirements and deliver effective technical solutions. Provide technical mentorship and guidance to junior data engineers through code reviews, architectural discussions, and best practices. Evaluate and recommend new data engineering tools, technologies, and cloud solutions to improve efficiency, scalability, and long-term sustainability.

Qualifications Fluent in English and Bahasa Indonesia. Bachelor’s or Master’s degree in Computer Science, Software Engineering, Information Systems, or a related technical field. Minimum 4–6 years of experience in data engineering, building and operating data pipelines and data infrastructure at scale. Strong programming skills in Python, Java, or Scala for data pipeline development and automation. Advanced proficiency in SQL and experience with relational and NoSQL databases (e.g., PostgreSQL, MySQL, MongoDB). Hands-on experience with ETL/ELT frameworks and big data tools such as Airflow, dbt, Spark, Kafka, or similar technologies. Experience working with cloud platforms (AWS, GCP, or Azure) and data services such as S3, Redshift, BigQuery, Databricks, or equivalents. Solid understanding of data modeling concepts, including dimensional modeling, normalization, and schema design. Familiarity with version control (Git) and CI/CD practices for deploying data pipelines. Knowledge of data governance, security, and compliance requirements, preferably within fintech or payments environments. Strong problem-solving skills with the ability to troubleshoot complex data issues in distributed systems and API integrations.