Staff Data Engineer

We’re hiring a Staff Data Engineer to lead the design and evolution of our global data platform. In this role, you’ll build the data foundations that support analytics, real-time processing, and AI-driven insurance products at massive scale.

You’ll work across data engineering and AI infrastructure, creating systems that power recommendations, claims automation, fraud detection, and vector-based search for 200M+ users across highly regulated markets.

Data Architecture & Engineering

• Design scalable, long-term data architectures that align with business goals and regional regulatory requirements

• Build and operate reliable data pipelines for ingestion, transformation, and consumption using modern data frameworks and orchestration tools

• Design data platforms covering data lakes, data warehouses, and real-time analytics use cases

• Define and maintain conceptual, logical, and physical data models using industry-standard methodologies

• Document and maintain a clear view of the enterprise data landscape, including data flows across microservices

AI & ML Data Infrastructure

• Develop and maintain data platforms supporting ML training, deployment, and monitoring workflows

• Design and implement vector-based data solutions for AI features such as semantic search and recommendations

• Build data pipelines enabling automation use cases including claims processing and fraud detection

• Ensure AI and data platforms scale globally while complying with data residency and regulatory constraints

Data Operations & Quality

• Establish DataOps practices to ensure data quality, governance, lineage, and reliability

• Define and enforce data architecture standards across engineering teams

• Implement monitoring and alerting for pipeline health, data accuracy, and SLA adherence

• Improve performance and optimize cost across data storage and query layers

Technical Leadership

• Partner with product and engineering teams to convert business needs into data solutions

• Drive adoption of modern data engineering practices across the organization

• Participate in architectural reviews and contribute to key technical decisions

• Take ownership of complex data issues through investigation and resolution

What We’re Looking For

Experience

• 8–10 years in data engineering, including ownership of architecture and technical leadership

• 3–5 years in startup environments, building and scaling data platforms in fast-moving teams

• Recent experience in insurance, banking, fintech, or e-commerce — insurance domain experience strongly preferred

• Proven success delivering data platforms that support production AI/ML workloads at scale

Technical Skills — Data Engineering

• Strong hands-on experience with cloud data services on AWS and Azure (multi-cloud required)

• Advanced experience with MongoDB Atlas, including aggregation pipelines, data federation, and document-based data modeling

• Hands-on expertise with data processing and orchestration tools such as Airflow, Spark, and Kafka

• Experience using dbt or similar transformation frameworks

• Strong SQL and Python skills

• Experience with Infrastructure as Code (Terraform) and Git-based workflows

• Practical knowledge of Docker and Kubernetes for running data workloads

Technical Skills — AI & ML Infrastructure

• Experience building data pipelines supporting ML training and inference workflows

• Hands-on work with vector databases (e.g. MongoDB Atlas Vector Search, Pinecone, Weaviate, Qdrant)

• Familiarity with MLOps concepts including model lifecycle management, feature stores, monitoring, and experimentation

• Solid understanding of embedding-based systems and retrieval-augmented generation (RAG) architectures

• Regular use of AI-assisted development tools such as GitHub Copilot, Claude, or Cursor

Professional Skills

• Strong data modeling and architectural thinking, with the ability to explain designs clearly to diverse stakeholders

• Self-driven and capable of managing priorities independently

• Comfortable collaborating across engineering, product, and business teams

• Startup-oriented mindset: adaptable, able to context-switch, and motivated by building new systems

What We Offer

• Competitive, market-aligned compensation

• Health insurance coverage for you and two family members

• Monthly meal and transportation allowances

• Performance-based annual bonus

• Modern office in Ho Chi Minh City

• International working environment with teams across Switzerland, Singapore, Vietnam, Portugal, and Latin America

• Modern data stack including MongoDB Atlas, multi-cloud infrastructure (AWS/Azure), and advanced DataOps practices

• Opportunity to build data infrastructure supporting 200M+ customers worldwide