Your Role

• Harness your expertise in data engineering and cloud infrastructure to design, build, and maintain scalable data platforms on Google Cloud Platform (GCP) for clients.
• Based in Vietnam, working closely with our regional and Singapore-based teams to deliver impactful data solutions.
• Make an outstanding contribution to a world-class AI and data team.
• Develop and maintain relationships with a broad range of clients, colleagues, and partners across a variety of contexts and formats.
• Invest continuously in building and extending your knowledge and skills.

Your Background

• At least 3–7 years of relevant working experience in data engineering, software engineering, or a related technical field.
• Proven track record in data engineering fundamentals: Python, SQL, ETL/ELT pipeline design, data modeling, and data integration.
• Hands-on experience with Google Cloud Platform (GCP), including data services (BigQuery, Cloud Storage, Dataflow, Dataproc, Pub/Sub, Dataplex) and infrastructure/deployment (Cloud Functions, Cloud Run, GKE, Cloud IAM).
• At least 3 years of implementation experience with serverless computing, CI/CD, containerisation, Infrastructure as Code, code version control and automated testing.
• Experience working with transactional databases (e.g., PostgreSQL, MySQL, SQL Server).
• Familiarity with AI/ML concepts and ability to support data pipelines for ML workloads (e.g., Vertex AI).
• Pro-active, curious personality with a strong desire to learn and grow.
• Good English communication skills, ability to communicate with clients and stakeholders effectively.

Data Engineering & DevOps

• Practical hands-on experience with data pipeline and orchestration tooling: Apache Airflow / Cloud Composer, Dataflow, Dataproc, dbt, Spark, or similar.
• Experience with data lake and warehouse architectures using BigQuery, Cloud Storage, and Dataplex.
• DevOps practices including containerisation (Docker, GKE), Infrastructure as Code (Terraform, Deployment Manager), and automated testing.
• Experience with streaming data platforms (e.g., Apache Kafka, Pub/Sub) is a plus.

Data Quality & Governance

• Strong focus on code quality, system reliability, and data governance.
• Experience with data quality checks, monitoring, alerting, and data lineage.
• GCP certifications (e.g., Google Cloud Professional Data Engineer, Professional Cloud Architect) are a plus.

AI Engineering (LLM & Agentic Systems)

• Practical hands-on experience with LLMs and agentic tooling: LangChain, LangGraph, AutoGen, CrewAI, OpenAI API, Anthropic API, Google Vertex AI, Hugging Face Transformers, MLFlow, Dataiku, MS Fairlearn, Google PAIR.
• Experience with prompt engineering, fine-tuning, evaluation frameworks, and responsible AI tooling.