Data Engineer
Data engineer building the data foundation for VinFast's AI Mobility Assistant (ViTA): turning ad-hoc data drops into scheduled, dependable ingestion pipelines and data products (Vehicle360, trips, Customer360). Core stack: Python, SQL, Airflow 3, Spark/EMR, dbt, ClickHouse, and an S3 medallion lake on AWS.
- Compensation
- Not disclosed
- Location
- Hanoi, Vietnam
- Work setup
- Not specified
- Seniority
- Not specified
- Employment
- Contract
- Experience
- 3+ years
- Category
- Data engineering
- Posted
Skills
Must have
- 3+ years in data engineering with production pipelines actually run in production
- Strong Python and SQL
- Apache Airflow — written and operated own DAGs, understands backfill and catchup
- Spark / PySpark — handled datasets in the hundreds of gigabytes
- Data modeling — grain, keys, SCDs, fact vs dimension
- Can explain idempotency, partition strategy, late-arriving data, and handling unexpected upstream schema changes
- Practical AWS: S3, IAM, able to read and fix a permissions error
- Strong communication with data owners outside the team
Nice to have
- ClickHouse or another columnar OLAP engine: Druid, Doris, BigQuery, Redshift
- Data visualization — Metabase, Superset, Grafana or similar
- Building MCP servers or tools for AI agents
- EMR / Spark on serverless infrastructure, including job cost tuning
- Kafka or CDC
- Vehicle, IoT or telemetry data experience
- Enough English to read technical documentation
Full description
VinFast is a pioneering electric vehicle (EV) company committed to revolutionizing the automotive industry with sustainable and innovative mobility solutions. As a leading player in the EV market, VinFast is dedicated to delivering high-quality, cutting-edge electric vehicles that redefine the driving experience. Our team consists of passionate professionals driven by a shared vision of creating a greener and more sustainable future through innovation, technology, and excellence.
**The mission
Build the data foundation for VinFast's AI Mobility Assistant (ViTA) and the AI agents running across the VinFast ecosystem.
To be direct about where we are: this platform is in its foundation phase, not its optimisation phase. One reference lane — vehicle telemetry — runs end to end from S3 through ClickHouse into dbt. The other ten registered sources have no recurring feed at all. Most of your job is turning ad-hoc data drops into scheduled, dependable feeds, not tuning dashboards.
If you want a stable system to operate, this isn't it. If you want to be the person who builds it, this is exactly it.
**What you'll be responsible for
- Data acquisition & integration
- Build ingestion pipelines for: vehicle telemetry, DMS / work-order history, CRM / O2O, charging, service, navigation.
- Work directly with source owners to settle the data contract: grain, keys, cadence, and how a changed record is identified.
- Read from S3, BigQuery and Redshift in batch — hive-partitioned and safe to re-run.
**2. Data platform
- Airflow 3 (MWAA) — asset-driven orchestration, no sensors.
- Spark / EMR Serverless — heavy preprocessing.
- dbt (ClickHouse adapter) — staging and mart layers.
- ClickHouse (MergeTree) and an S3 medallion lake.
- Guarantee idempotency, correct partitioning, safe re-runs and backfills, and predictable cost.
**3. Data products
- Built in priority order — not all at once:
- Vehicle360 — in progress
- Mobility360 / trips — in progress
- Customer360 — blocked pending the identity spine and consent decisions
- Charging360, Service360 — backlog
- Every data product needs a clear schema, tests, documentation, and an owner.
**4. Serving & data access