# Data Engineer

> Qode · Vietnam (Remote) · Full-time · Posted 2026-05-07

**Workplace:** remote

## Description

**About the role**

We are looking for a **Data Engineer** to join our Data Platform team, focusing on building scalable data pipelines and enabling analytics across the organization.

In this role, you will work with modern data stack tools like **Databricks, AWS, Airflow, Airbyte, and dbt** to design and maintain data workflows that support reporting, analytics, and data-driven decisions.

This is a good fit if you enjoy working with large-scale data systems, building reliable pipelines, and optimizing performance in a cloud-based environment.

  

**Your Responsibilities**

-   Design and build scalable ETL/ELT pipelines using both batch and streaming approaches
-   Develop ingestion workflows from multiple sources such as databases, APIs, and event streams
-   Implement ingestion strategies including full load, incremental load, and CDC
-   Orchestrate data workflows using Apache Airflow
-   Manage data connectors using Airbyte
-   Work with Databricks Lakehouse to build and optimize data processing pipelines
-   Write and optimize complex SQL queries for analytics and transformation
-   Build modular and testable data models using dbt (staging → intermediate → marts)
-   Maintain data quality, observability, and reliability across the platform
-   Work with AWS services such as S3, Lambda, EC2, IAM
-   Containerize data services using Docker and Kubernetes (EKS) when needed
-   Document pipelines, data models, and data dictionaries for long-term maintainability

  

**Requirements**

-   **At least 4 years of experience in Data Engineering**
-   Strong understanding of **data architectures** such as Data Lake, Data Warehouse, and Lakehouse
-   Hands-on experience with **ETL/ELT pipelines**, including batch and streaming processing
-   Familiar with ingestion patterns: full load, incremental, CDC, event-driven
-   Experience working with **Databricks** (Delta Live Tables, Jobs, Notebooks)
-   Strong skills in **PySpark or Spark SQL** for large-scale data processing
-   Solid understanding of Delta Lake (ACID, time travel, schema evolution)
-   Experience with Apache Airflow (DAGs, scheduling, monitoring)
-   Experience with Airbyte or similar ingestion tools
-   Strong SQL skills (CTEs, joins, window functions, query optimization)
-   Experience with **dbt** for transformation, testing, and documentation
-   Hands-on experience with **AWS** (S3, Lambda, IAM, etc.)
-   **Be proficient in English communication skills (at least C1 level)**

**_Nice to Have_**

-   Experience with Docker, Kubernetes (EKS)
-   Experience running Airflow or Airbyte on Kubernetes
-   Familiar with data quality tools such as Great Expectations or Soda
-   Experience with Terraform or Infrastructure as Code
-   Exposure to data governance or catalog tools (e.g., Databricks Catalog)
-   Experience with CI/CD pipelines (e.g., GitHub Actions)
-   Strong Python skills for automation and pipeline scripting

  

**👉 Our Benefit Packages:**

-   Attractive salary range and we are open to negotiate if you're a strong fit.
-   Hybrid/Remote-friendly culture, work where you grow best!
-   Flexible hours, async teamwork (we respect your focus time)
-   Work equipment support
-   Allowance for Certification & Skill Development
-   Year-end bonus & performance-based rewards
-   22 paid leaves from your 5th year - take a full month off
-   Career growth with personal coaching sessions
-   Open, collaborative team culture - no micromanagement, only trust
-   Tools & AI-powered workflows that make remote work easier

  

**About CoderPush**

**CoderPush** is a remote-first technology company that partners with startups and global businesses to build scalable, high-quality software products. We focus on long-term collaboration, clear communication, and delivering real impact through strong engineering and product thinking.

Please find more at: https://coderpush.com/

## Apply

[Apply at Qode](https://apply.workable.com/qodeworld/j/387AFE26CB/apply)

---
Powered by [Workable](https://www.workable.com)