Mid-Senior Software Engineer

Vietcetera is seeking a Mid–Senior Software Engineer with strong backend and data engineering expertise to design and build the technical foundation of our audience data ecosystem.

You will architect and maintain systems that ingest, process, store, and expose data from multiple sources — powering analytics, personalisation, and AI-driven initiatives across Marketing, Product, and Editorial.

This is a highly technical role focused on backend systems, APIs, data pipelines, and cloud infrastructure. You will have significant ownership in shaping how data flows and how internal teams access and use it.

1. Backend Engineering

• Design, build, and maintain backend services supporting data ingestion, transformation, and delivery. 

• Develop internal APIs enabling Marketing, Content, Product, and Data teams to access unified audience information.

• Build and optimize RESTful APIs using Node.js (Express/NestJS) that serve our Website (React) and Mobile App (React Native).

• Implement logic for high-impact features like the new AI-powered, User Personalization and connect data pipelines to our Warehouse.

2. Data Pipeline Development

• Build scalable ETL/ELT pipelines connecting GA4, CMS, CRM, Email/SMS systems, Social APIs, and Event platforms.

• Handle batch and streaming ingestion where needed (webhooks, cron jobs, queues).

• Ensure data consistency, schema evolution, and error handling mechanisms.
  
  

3. Cloud Infrastructure (GCP preferred)

• Work with BigQuery for data warehousing, schema design, partitioning, and performance optimization.

• Deploy and manage microservices using Cloud Run / Kubernetes / App Engine.

• Set up monitoring (Stackdriver), logging, alerting, and dashboarding for pipeline health.
  
  

4. Automation & Internal Tools

• Build internal tools that automate repetitive workflows for Marketing, Content, Editorial, and Ops.

• Implement background jobs for data syncing, enrichment, deduplication, and segmentation.

• Support integration with AI workflows (vector search, embeddings, LLM-powered enrichment).
  
  

5. System Reliability & Maintenance

• Establish CI/CD pipelines (GitHub Actions or similar).

• Own the quality, performance, and reliability of the data infrastructure.

• Document system architecture, integration specs, and maintenance playbooks.
  
  

6. Cross-functional Collaboration

• Work closely with Data Analyst to align on data structure, metrics, and schema evolution.

• Collaborate with Product and Marketing teams to understand business requirements and translate them into system capabilities.

• Collaborate with Frontend developers to build internal dashboards (for the editorial/data team) or debug integration issues between the API and the Client side.

Experience

• 3–6+ years as Backend Engineer or Data Engineer.

• Experience with high-volume data systems, APIs, or cloud-based architectures.
  
  

Core Technical Skills

• Backend: Node.js (preferred), Python, or Go.

• API Development: RESTful API design, authentication (OAuth2/JWT), rate limiting.

• Cloud: Google Cloud Platform preferred (Cloud Run, Pub/Sub, BigQuery).

• Data Pipelines: ETL/ELT design, message queues, cron jobs, webhooks.

• Databases: SQL + at least one NoSQL datastore.

• DevOps: Docker, CI/CD pipelines, container-based deployment.

• Version Control: Git, GitHub workflow.
  
  

Nice-to-Haves

• Experience with Airflow, dbt, Temporal, or equivalent orchestration tools.

• Experience with GA4 Reporting API, Meta/TikTok APIs, CRM APIs (HubSpot/Pipedrive).

• Familiarity with vector databases or embedding-based similarity search.

• Understanding of LLM integrations for automation or enrichment tasks.
  
  

Soft Competencies

• Strong problem-solving and debugging instincts.

• Ownership mindset — comfortable managing systems end-to-end.

• Clear communication, especially when working with non-technical stakeholders.

• Pragmatic approach balancing speed and scalability.