Data Engineer (Operations focused)

Handshakes is an award-winning DataTech company. We enable our clients to make safer, more informed decisions by delivering meaningful insights, harnessed from reliable data.
We are currently hiring a Data Engineer (Operations focused) to safeguard the health, reliability, and accuracy of our production data ecosystem while contributing directly to new data pipeline developments.
This is a hybrid role (80% Operations & Support / 20% Pipeline Projects) tailored for an engineer who excels at troubleshooting, system reliability, and automation, but also wants to stay hands-on with pipeline design and implementation.
Position is based in Hanoi and we have a work arrangement of 3 days work in office on hybrid working as per company policy.
Key Responsibilities
Data Operations & System Reliability
Pipeline Monitoring & Incident Response: Monitor daily ETL/ELT batch and streaming data pipelines, proactively handling run failures, schema drifts, and latency delays.
Data Quality & Triage: Investigate data quality issues, trace root causes across pipelines and data warehouses, and resolve support tickets from business analytics teams.
Operational Automation: Identify recurring operational manual tasks and build scripts or automated checks to eliminate repetitive work.
System Maintenance: Assist with pipeline performance tuning, resource optimization (compute/storage costs).
Pipeline Projects & Enhancements
New Pipeline Development: Partner with core Data Engineers to build, test, and deploy new data ingestion feeds and ETL/ELT pipelines.
Refactoring: Modernize and optimize existing production pipelines to improve maintainability and scalability.
Skills & Experiences
Bachelor's degree in Computer Science, Information Systems, Engineering, or relevant hands-on technical experience.
Years of Experience: Minimum 1 - 2 years experience in the related function Fresh graduates are welcome to apply.
SQL & Scripting: Strong proficiency in SQL and Python (or Bash) for data manipulation, scripting, and pipeline development.
Technical: Exposure to cloud platforms (AWS), containerization tools like Docker and version control (git)
Troubleshooting Mindset: Strong analytical and debugging skills to diagnose complex data pipelines under tight SLAs.
Communication: Ability to communicate clearly with both technical and business stakeholders during incident response.
Nice-to-Have Skills
Experience with CI/CD tools and infrastructure-as-code (e.g., Terraform).