Data Engineer - GCP

As a Data Engineer with 3+ years of experience, your role will involve building and managing data pipelines, data models, and cloud-based analytics solutions on Google Cloud Platform (GCP). You should have expertise in GCP-native services such as BigQuery, Dataflow, Pub/Sub, Cloud Storage, and Composer. Your responsibilities will include collaborating with data scientists, analysts, and business teams to ensure scalable and high-performance data infrastructure. Key Responsibilities: - Design, build, and optimize scalable ETL/ELT pipelines using GCP services (Dataflow, Composer, Pub/Sub, BigQuery). - Ingest structured and unstructured data from multiple sources into cloud storage and warehouse solutions. - Develop efficient and optimized data models in BigQuery. - Implement partitioning, clustering, and query optimization for performance and cost efficiency. - Work with GCP-native tools for data integration, storage, and analytics. - Ensure high availability, security, and compliance of data systems. - Partner with data scientists, analysts, and application teams to deliver reliable datasets. - Troubleshoot issues, monitor pipelines, and ensure SLAs for data delivery. - Implement data quality checks, monitoring, and lineage tracking. - Follow DevOps and CI/CD practices for data engineering projects. Required Skills & Qualifications: - 3+ years of hands-on experience in data engineering. - Strong expertise in GCP data services such as BigQuery, Dataflow, Cloud Composer, Pub/Sub, Cloud Storage, and Dataproc. - Proficiency in SQL and Python for data transformation and automation. - Good knowledge of ETL/ELT design, data modeling, and warehousing principles. - Experience with Git, CI/CD pipelines, and version control. - Understanding of data security, IAM, and compliance in cloud environments. Nice-to-Have Skills: - Familiarity with Terraform/Deployment Manager for Infrastructure as Code (IaC). - Knowledge of Kafka, Spark, or DBT for advanced data engineering use cases.,