Cloud Data Engineer Location: United States – Remote Work Hours: 40 hours/week Time Zone: Central or Eastern Time Job Summary We are seeking a highly skilled Cloud Data Engineer with deep expertise in Google Cloud Platform (GCP) data services and cloud data architecture. The ideal candidate will have hands-on experience designing scalable cloud data platforms, developing batch and real-time data processing solutions using Dataproc, Apache Spark, and Spark Streaming, and implementing enterprise data governance using Dataplex. The engineer will collaborate with engineering, architecture, and business teams to build and optimize modern data platforms supporting analytics, reporting, and AI/ML initiatives.

Key Responsibilities

Design and implement scalable, cloud-native data architectures on GCP. Develop and optimize batch and real-time data pipelines using Dataproc, Spark, and Spark Streaming. Configure and manage Dataplex for data governance, metadata management, lineage, and data quality. Design and maintain enterprise-scale data lakes and data warehouse solutions. Build robust data ingestion, transformation, and orchestration workflows. Collaborate with architects, engineers, and business stakeholders to define technical requirements and solution designs. Implement data security, governance, and compliance best practices. Troubleshoot performance issues and optimize cloud data workloads for scalability and efficiency. Create technical documentation, architecture diagrams, and implementation recommendations. Required Skills & Experience 8+ years of experience in Data Engineering and Cloud Data Platforms. Strong hands-on experience with Google Cloud Platform (GCP). Expertise in GCP Dataplex. Expertise in GCP Dataproc. Strong experience with Apache Spark and Spark Streaming. Proven experience designing enterprise-scale data architectures. Strong SQL and Python programming skills. Experience with cloud-based data lakes, data warehouses, ETL/ELT, and data pipelines. Strong understanding of data governance, security, metadata, lineage, and data quality. Excellent troubleshooting, analytical, and communication skills.

Preferred Qualifications

Experience supporting analytics, reporting, and AI/ML data platforms. Experience with large-scale distributed data processing. Knowledge of GCP data services and cloud-native architecture patterns. Experience creating architecture diagrams and technical design documentation.