About the Role

We are looking for an experienced Data Engineer with deep expertise in Google Cloud Platform (GCP) to design, build, and manage end-to-end data systems that drive analytics, business intelligence, and AI initiatives.

In this role, you’ll be responsible for building high-performance data pipelines that handle data ingestion, transformation, and integration (ETL/ELT) across multiple systems. Beyond ETL, you will design the broader data infrastructure, including data lakes, workflow orchestration, API-driven integrations, and CI/CD automation to ensure scalability, reliability, and seamless data flow across the enterprise.
This is a hands-on engineering position that blends data architecture, software engineering, and cloud infrastructure expertise. You’ll collaborate closely with analytics, data science, and product teams to enable a modern, data-driven ecosystem.

Key Responsibilities
● Design and develop scalable data pipelines using GCP services such as BigQuery, Dataflow (Apache Beam), Pub/Sub, Dataproc, and Cloud Composer (Airflow).
● Implement end-to-end ETL/ELT workflows that extract data from multiple sources, transform it into meaningful formats, and load it into data warehouses or data lakes.
● Architect and maintain data lake environments using Cloud Storage and integrate with downstream analytical tools.
● Automate data ingestion frameworks from APIs, streaming platforms, and external systems into the cloud.
● Implement workflow orchestration and job automation with Airflow/Cloud Composer to ensure smooth and reliable pipeline execution.
● Enable real-time data streaming and event-driven processing using Pub/Sub, Kafka, or Dataflow.
● Collaborate with analytics and ML teams to design data models, feature stores, and data marts that power reporting and AI solutions.
● Develop API-based data services and reusable connectors to enhance cross-platform data accessibility.
● Integrate CI/CD best practices for data pipelines, including testing, versioning, and automated deployment through Git, Terraform, and Cloud Build.
● Establish data governance, lineage, and observability frameworks to ensure data quality, security, and compliance.

Required Skills & Experience
● 4–7 years of experience in data engineering or ETL development with large-scale data systems.
● Strong proficiency in Google Cloud Platform (BigQuery, Dataflow, Pub/Sub, Dataproc, Cloud Storage, Composer).
● Solid understanding of ETL/ELT design principles, data modeling, and data warehouse architecture.
● Proficiency in Python, SQL, and experience with distributed data processing frameworks (Apache Beam, Spark).
● Experience building data lakes and managing schema evolution in structured and semi-structured data (JSON, Parquet, Avro).
● Skilled in workflow orchestration (Airflow, Dagster, or Prefect) and infrastructure automation (Terraform, Cloud Deployment Manager).
● Familiarity with API integrations, event streaming, and real-time data processing.
● Google Professional Data Engineer Certification or equivalent.
● Experience with modern data stack tools like DBT, Looker, or Dataform.
● Familiarity with machine learning data pipelines or feature engineering workflows.


本職缺為派遣工作，求職者個人履歷資料將作為推薦要派工作之用。

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