As a Data Engineer at Apply Digital, you will contribute to building and maintaining cloud-native data pipelines that support our Composable digital platforms, working with cross-functional teams to deliver scalable solutions.

In Short

Design, develop, and maintain data pipelines for ETL/ELT/Streaming workflows.
Collaborate with backend and platform engineers to integrate data solutions into cloud-native applications.
Optimize data storage, retrieval, and processing for performance and cost efficiency.
Operate cloud data infrastructure, primarily Google Cloud Platform (BigQuery, Cloud Storage, Pub/Sub).
Work with analytics and product teams to define data models for reporting and business intelligence.
Implement data security, privacy, and governance best practices.
Monitor, troubleshoot, and enhance data pipeline reliability and performance.
Maintain clear documentation for data pipelines, transformations, and data sources.
Stay updated with best practices and emerging technologies in data engineering.

Requirements

Strong proficiency in English (written and verbal communication) is required.
Experience working with remote teams across North America and Latin America.
3+ years of experience in data engineering, focusing on building scalable pipelines and cloud-native architectures.
Strong SQL skills for data modeling, transformation, and optimization.
Proficiency in Python for data processing and automation.
Experience with cloud data platforms, particularly Google Cloud Platform (GCP).
Hands-on experience with Google BigQuery, Cloud Storage, and Pub/Sub.
Familiarity with ETL/ELT tools such as DBT, Apache Beam, or Google Dataflow.
Exposure to data pipeline orchestration tools like Dagster, Apache Airflow, or Google Cloud Workflows.
Knowledge of data privacy, security, and compliance practices.