Source description
About the role
Job Summary We are looking for an experienced GCP Data Engineer with 612 years of expertise in designing, developing, and maintaining scalable data pipelines and modern cloud-based data platforms on Google Cloud Platform (GCP). The ideal candidate should have strong experience in building batch and real-time data processing solutions, optimizing data workflows, and enabling analytics through robust data engineering practices. Key Responsibilities Design, develop, and maintain scalable data pipelines using GCP services. Build and optimize ETL/ELT workflows for structured, semi-structured, and unstructured data. Develop cloud-native data solutions using BigQuery, Cloud Storage, Dataflow, Dataproc, Pub/Sub, and Composer. Implement batch and streaming data pipelines using Apache Beam and Dataflow. Design high-performance data models for analytics and reporting. Optimize BigQuery queries for cost, performance, and scalability. Integrate data from multiple enterprise systems, APIs, databases, and third-party applications. Ensure data quality, governance, security, and compliance across the data platform. Implement CI/CD pipelines for data engineering solutions using Git, Cloud Build, or Jenkins. Monitor, troubleshoot, and optimize production data pipelines. Collaborate with data architects, analysts, data scientists, and business stakeholders to deliver scalable solutions. Participate in code reviews, architecture discussions, and best practice implementation. Mandatory Skills Google Cloud Platform (GCP) BigQuery Cloud Storage (GCS) Dataflow Dataproc Pub/Sub Cloud Composer (Apache Airflow) Apache Beam Python SQL ETL/ELT Development Data Modeling Git CI/CD Performance Tuning Data Warehousing Concepts Good to Have Skills Apache Spark Kafka Terraform Docker Kubernetes (GKE) Looker Looker Studio Cloud Functions Cloud Run Vertex AI exposure dbt Snowflake Delta Lake Apache Iceberg Required Qualifications Bachelor's or Master's degree in Computer Science, Information Technology, or a related field. 6–12 years of experience in Data Engineering. Minimum 3+ years of hands-on experience with Google Cloud Platform (GCP). Strong expertise in SQL and Python. Experience building enterprise-scale data pipelines and cloud data warehouses. Knowledge of distributed data processing frameworks. Experience with data security, governance, and access management. Familiarity with Agile/Scrum methodologies. Preferred Certifications Google Professional Data Engineer Google Associate Cloud Engineer Google Professional Cloud Architect Key Competencies Strong analytical and problem-solving skills. Excellent communication and stakeholder management. Ability to work independently and within cross-functional teams. Strong debugging and performance optimization skills. Ownership mindset with attention to quality and scalability.
More at Elabs Infotech