Bandung, Indonesia
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.
You'll design, build, and maintain the data systems that power our global programs — from pipelines to analytics-ready warehouses — covering full-cycle engineering, performance optimization, and governance. You'll operate with a high degree of independence, make sound decisions without waiting for direction, and ship reliable solutions in a fast-moving environment. This is a role for someone who leads by doing.
Our Stack
We've Standardized Our Platform Deliberately, And We Want Someone Who's Strong In These Tools — Not Someone We Have To Retrain On The Fundamentals
- Cloud: Google Cloud Platform (GCP)
- Data warehouse: BigQuery — this is the heart of everything we do, and deep hands-on experience here is required
- Orchestration: Apache Airflow (Cloud Composer)
- Transformation & modeling: dbt (or Dataform)
- Sources: MongoDB (application database) and other operational sources
- BI & visualization: Looker Studio and Metabase
- Languages: Python and SQL
- Streaming (where needed): Pub/Sub
- Version control & delivery: Git, with CI/CD for data workflows
- AI tooling: Claude and other LLM assistants used daily to move faster
Before You Apply
We want to be upfront about how we work. This role moves quickly and trusts you with real ownership. You'll handle ambiguity, juggle multiple priorities, and deliver production-ready work — sometimes as requirements shift mid-week or feedback needs a fast turnaround. We look for people who stay composed under pressure, take full accountability for their work, and hold themselves to a high standard without close supervision.
If you're looking for a role that will stretch your technical range, sharpen your problem-solving, and connect your work to a mission that matters, we'd love to hear from you.
Responsibilities
Data Infrastructure & Pipelines
- 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.
Performance & Reliability
- 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.
Data Quality & Governance
- 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.
Analytics & BI Enablement
- 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.
AI-Enhanced Workflows
- 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.
Collaboration & Documentation
- 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 — this is non-negotiable, as it's the core of our platform.
- 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.
Why Join Us?
You'll be joining a team with a bold mission to transform education. We don't expect perfection, but we do expect creativity, ownership, and a strong learning attitude. If you're looking for a conventional engineering role, this may not be the right fit. But if you're ready to lead with technology, build innovative solutions, and create real-world impact — we'd love to hear from you.
