Data Engineer

About the Role

Solve Education! is hiring a Data Engineer to build and own the data infrastructure behind our mission: helping young people everywhere reach their potential through accessible, AI-powered learning. This is a high-ownership role for an engineer who thrives on autonomy, sets a high bar for their own work, and wants their engineering to translate directly into real-world impact.

Bandung, Indonesia

Employment Type: Full-Time

Responsibilities

• Design, build, and maintain scalable pipelines in Apache Airflow to ingest data from multiple sources — including MongoDB — into BigQuery.
• Own the data architecture across ingestion, storage, and transformation layers, keeping it reliable, consistent, and high-quality.
• Model raw data into clean, structured, ready-to-consume datasets using dbt/Dataform, including turning event-level data into sessions and other analytical entities.
• Build and curate data sources and data marts that serve analytical and reporting needs across teams.
• Monitor pipeline health, troubleshoot failures, and ensure timely, accurate data delivery with minimal downtime.
• Optimize BigQuery query performance and manage storage/compute cost to keep the platform efficient.
• Implement automated testing, validation, and error handling to keep pipelines robust.
• Apply best practices in data modeling, security, and compliance, and safeguard data integrity across the platform.
• Implement governance, access controls, and documentation (metric definitions, lineage, business glossary) for secure, consistent data usage.
• Build dashboards and visualizations in Looker Studio and Metabase to support data-driven decisions.
• Partner with stakeholders to define metrics and enable reliable self-service analytics.
• Use AI-powered tools (e.g., Claude, GitHub Copilot, cloud-native AI services) to boost efficiency, scalability, and documentation quality.
• Continuously explore and adopt new technologies that streamline workflows and accelerate delivery.
• Work closely with product, engineering, and business teams to define data requirements, metrics, and self-service analytics needs.
• Translate business requirements into efficient, scalable technical solutions, enabling advanced analytics and ML initiatives.
• Maintain technical documentation and standards, track key performance metrics, and propose evidence-based improvements to the platform.

What We're Looking For

• 2–4 years of experience in data engineering, database development, or related technical roles.
• Strong command of SQL and Python, with solid software-engineering habits.
• Deep, hands-on experience with BigQuery is required.
• Hands-on experience with workflow orchestration in Apache Airflow.
• Experience modeling and transforming data with dbt or Dataform.
• Experience building dashboards in Looker Studio and/or Metabase.
• Working knowledge of GCP and experience with both relational and non-relational databases (e.g., MongoDB).
• Tech-savvy, with a habit of learning and applying AI tools in daily work.
• Ability to manage multiple priorities independently and under pressure, with high attention to detail, personal accountability, and strong problem-solving skills.

Bonus Points If You Have

• Real-time data streaming and event-driven architectures (e.g., Pub/Sub, Kafka).
• Experience standing up CI/CD pipelines for data engineering.
• Exposure to MLOps or machine learning pipeline deployment.
• A demonstrated track record of using AI tools (Claude, Copilot, LLM-based assistants, automation frameworks) to accelerate engineering work.
• Experience in mission-driven or non-profit organizations.