Job
Description
Position Overview: The Google Cloud Data Engineering Lead role is ideal for an experienced Google Cloud Data Engineer who will drive the design, development, and optimization of data solutions on the Google Cloud Platform (GCP). The role requires the candidate to lead a team of data engineers and collaborate with data scientists, analysts, and business stakeholders to enable scalable, secure, and high-performance data pipelines and analytics platforms. Key Responsibilities: Lead and manage a team of data engineers delivering end-to-end data pipelines and platforms on GCP. Design and implement robust, scalable, and secure data architectures using services like BigQuery, Dataflow, Dataproc, Pub/Sub, and Cloud Storage. Develop and maintain batch and real-time ETL/ELT workflows using tools such as Apache Beam, Dataflow, or Composer (Airflow). Collaborate with data scientists, analysts, and application teams to gather requirements and ensure data availability and quality. Define and enforce data engineering best practices including version control, testing, code reviews, and documentation. Drive automation and infrastructure-as-code approaches using Terraform or Deployment Manager for provisioning GCP resources. Implement and monitor data quality, lineage, and governance frameworks across the data platform. Optimize query performance and storage strategies, particularly within BigQuery and other GCP analytics tools. Mentor team members and contribute to the growth of technical capabilities across the organization. Qualifications: Education : Bachelor’s or Master’s degree in Computer Science, Data Engineering, or related field. Experience : 7+ years of experience in data engineering, including 3+ years working with GCP data services. Proven leadership experience in managing and mentoring data engineering teams. Skills : Expert-level understanding of BigQuery, Dataflow (Apache Beam), Cloud Storage, and Pub/Sub. Strong SQL and Python skills for data processing and orchestration. Experience with workflow orchestration tools (Airflow/Composer). Hands-on experience with CI/CD, Git, and infrastructure-as-code tools (e.g., Terraform). Familiarity with data security, governance, and compliance practices in cloud environments. Certifications : GCP Professional Data Engineer certification.
