Data Engineer

Company Overview

AwanTunai is the leading vertical fintech player digitizing the offline FMCG supply chain in Indonesia. We solve for both operational and financing pain points through ERP software and integrated embedded financing for offline suppliers. Our traditional suppliers have aggregate annual sales of over $3bn+ and our embedded financing is on track to reach the annualized $1bn milestone next quarter. We have been growing revenues at an average 30% QoQ with 0.2% credit loss rates over the pandemic period across hundreds of traditional suppliers.

Our financial impact has won accolades from the UNCDF, Monetary Authority of Singapore, and with the IFC (World Bank Group) as a major shareholder. Management and our impact focused shareholders are committed to building a world class team regardless of diversity or location. 

Our fraud management has won the trust of global banking groups (MUFG, OCBC), the largest local institutions (Bank BRI, Bank Mandiri), as well as global insurers (AA rated Munich Re) who protect our loan assets against credit default.

Role

AwanTunai is looking for a Data Engineer who will be responsible for the design, implementation, and maintenance of data processing systems  that enables downstream machine learning and BI systems.

Responsibilities

• Develop, maintain, and optimize ETL pipelines to enable efficient data processing and integration.

• Work closely with data scientists and engineers to ensure data availability and reliability.

• Implement data quality checks, monitoring, and validation processes to maintain data integrity.

• Optimize database performance and manage structured and unstructured datasets.

• Develop and maintain data APIs and integrations to facilitate seamless data exchange across systems.

• Ensure compliance with data security and governance policies.

Requirements

• Bachelor’s degree in Computer Science, Information Systems, or a related field.

• Strong problem-solving skills and ability to work collaboratively in a fast-paced environment.

• 3+ years of professional working experience in industry on data engineering, data warehousing, or related roles 

• Strong experience with SQL and database technologies (MySQL, PrestoDB, MongoDB).

• Proficiency in Python and libraries for data processing and automation.

• Hands-on experience with ETL tools and workflow orchestration (Airflow, Cronjobs).

• Experience with cloud platforms (GCP or AWS).

• Proficiency in BI and data dashboarding  tools (Superset, Metabase, Tableau, Yanagishima).

• Familiarity with data modeling, schema design, and performance optimization.

• Experience with Postman for API testing and integration.

• Knowledge of Git for version control and collaboration.