Data Backend Engineer: Build Scalable Pipelines

Wati; Hong Kong; On-site; HKD 450,000 - 750,000; Full time

Benefits offered by this job

ML/AI model integration

Data governance and security practices

BI tools familiarity (Tableau/Looker/​

Job summary

Wati is seeking a Data Backend Engineer to join our China team and strengthen our data infrastructure. You will work on large-scale data systems to enable insights and analytics across our platform.

Role requires 2–4 years of backend/data engineering experience and strong skills in Python, Java, or Go, plus SQL/NoSQL expertise. Collaboration with product and analytics teams is key to delivering data-driven features.

Qualifications

• Bachelor's or Master's in Computer Science, Data Engineering, or related field.
• 2–4 years of backend/data engineering experience.
• Proficiency in Python, Java, or Go.
• Hands-on experience with SQL and NoSQL databases (MongoDB, PostgreSQL, BigQuery).
• Familiarity with ETL pipelines, data warehousing, and streaming frameworks (Kafka, Spark, Flink).
• Understanding of cloud-based data infrastructure (GCP, AWS, or Azure).

Responsibilities

• Build and maintain scalable data pipelines and backend services.
• Design and optimize data storage solutions (structured and unstructured).
• Collaborate with product and analytics teams to deliver data-driven features.
• Ensure data quality, availability, and performance at scale.
• Integrate with third-party APIs and tools for reporting and analytics.

Skills

Python

Java

Go

SQL

NoSQL

ETL

Data warehousing

Kafka

Spark

Flink

Cloud platforms

BigQuery

Education

Bachelor's or Master's in CS or related field

Tools

MongoDB

PostgreSQL

BigQuery

Tableau

Looker

Metabase

Job description

Wati is seeking a Data Backend Engineer to join our China team and strengthen our data infrastructure. You will work on large-scale data systems to enable insights and analytics across our platform.

Role requires 2–4 years of backend/data engineering experience and strong skills in Python, Java, or Go, plus SQL/NoSQL expertise. Collaboration with product and analytics teams is key to delivering data-driven features.