GCP Data Engineer

Job Description

Industry: Information Services, IT Services and IT Consulting, and IT System Data Services
Seniority for this role: Mid-Senior level
We are seeking a skilled GCP Data Engineer to support in the ESG transformation program. In this role, you will design, develop, and optimize data pipelines and systems using Google Cloud Platform (GCP) to build data products that will be used for the ESG reporting needs. You will collaborate with cross-functional teams to deliver high-quality, scalable data solutions that drive business insights and operational excellence. Key Responsibilities: Design and implement robust, scalable, and efficient data pipelines using GCP services such as BigQuery, Dataflow, Pub/Sub, Cloud Storage, and more. Build and maintain data models and ETL processes to support data analytics and reporting needs. Optimize data storage and retrieval for performance and cost-effectiveness. Collaborate with data scientists, analysts, and other engineers to understand data requirements and deliver solutions. Monitor and troubleshoot production pipelines to ensure data quality and system reliability. Implement security best practices to ensure data integrity and compliance with regulations. Create and maintain comprehensive documentation for data workflows, architecture, and systems. Qualifications: Must-Have Skills: 5+ years of experience in data engineering or related fields. Proficiency with GCP services, including but not limited to BigQuery, Dataflow, Cloud Storage, Cloud Composer (Airflow), and Pub/Sub. Strong programming skills in Python and Java. Hands-on experience with SQL for querying and transforming data. Knowledge of data modeling, data warehousing, and building scalable ETL/ELT pipelines. Familiarity with CI/CD pipelines for deploying and managing data workflows. Solid understanding of distributed computing and cloud-based architecture. Preferred Skills: Experience with other cloud platforms (AWS or Azure) is a plus. Knowledge of Spark, Hadoop, or other big data technologies. Familiarity with Kubernetes or containerised applications. Background in machine learning or data science is advantageous. Soft Skills: Excellent problem-solving skills and a proactive approach to challenges. Strong communication skills to explain technical concepts to non-technical stakeholders. Ability to work in a fast-paced environment with changing priorities. Team-oriented mindset with a passion for knowledge sharing. Show more Show less