Data Engineer (Data Platform) - Monee Credit
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Summary
Data engineer at Monee's credit/lending business in Indonesia, building and maintaining data pipelines, data marts, and self-service automation/AI products that support BI, analytics, and regulatory reporting. Core stack is Python, SQL, Spark, and Airflow, plus LLM/agentic tooling.
- You will work closely with Business Intelligence Analysts, project teams to turn data into information that supports sound business initiatives and to build automation products that meet business needs.
- Build and maintain data pipelines and data marts supporting Business Intelligence, Analytics, and Regulatory Reporting initiatives.
- You will own the full development lifecycle, implementation, and support of self-service data, business automation, and AI products.
- Design and maintain the architecture of a high-performing business automation and AI platform.
Job Description
- You will work closely with Business Intelligence Analysts, project teams to turn data into information that supports sound business initiatives and to build automation products that meet business needs.
- Build and maintain data pipelines and data marts supporting Business Intelligence, Analytics, and Regulatory Reporting initiatives.
- You will own the full development lifecycle, implementation, and support of self-service data, business automation, and AI products.
- Design and maintain the architecture of a high-performing business automation and AI platform.
- Follow software engineering best practices, including test-driven development.
Requirements
- Bachelor's degree in Computer Science or any related field with 2+ years of relevant experience working in Data Engineering, Software/AI Engineering, or related fields.
- Strong Python expertise, with emphasis on data ingestion and automation frameworks (e.g. Selenium, Playwright).
- Advanced skills in SQL, Spark, Airflow, and other data processing/engineering tools, familiarity with frontend development is a plus.
- Familiarity with LLM and Agentic tools and paradigms (e.g. agent harness), as well as its application in business.
- Proficient in Software Development Life Cycle (SDLC) including code version control, test-driven development, modularity, and technical documentation.
- Ability to translate complex technical concepts to non-technical stakeholders.
- Comfortable working with a variety of languages, frameworks, and technologies, adapting to the most suitable tool for the task at hand.
- Ability to converse in English is strongly preferred as we are deeply working with regional teams.