SeniorGCPDataEngineer

## Accountabilities Design, build, and maintain scalable ETL/ELT pipelines on Google Cloud Platform. Develop and optimize data models and architectures to ensure high performance, reliability, and scalability. Implement and manage large-scale data processing solutions using services such as BigQuery, Dataflow, and Pub/Sub. Maintain and improve data architecture, ensuring efficiency in storage, transformation, and querying processes. Apply data security best practices and ensure compliance with engineering and organizational standards. Collaborate with product and engineering teams to understand requirements and deliver data-driven solutions. Support tracking specifications and data requirements for product and feature development. Contribute to CI/CD pipeline implementation and support automated deployment processes. Troubleshoot and resolve complex data pipeline and infrastructure issues. Requirements: 5+ years of experience in data engineering or related software engineering roles. Strong hands-on experience with Google Cloud Platform services including BigQuery, Dataflow, Pub/Sub, Cloud Functions, and Memorystore/Redis. Strong knowledge of SQL and NoSQL databases, including data modeling, optimization, and performance tuning. Experience building and maintaining large-scale data pipelines and distributed data systems. Proficiency in programming languages such as Python and Java. Experience with CI/CD pipelines and modern DevOps practices. Familiarity with Agile/Scrum development environments. Strong analytical and problem-solving skills for complex technical challenges. Excellent communication skills in English, both written and verbal. Experience with tools such as Terraform and Kafka is a plus. Benefits: Collaborative and knowledge-sharing engineering culture Agile environment where innovation and ideas are encouraged Opportunity to work on large-scale cloud data platforms Continuous learning, training, and mentoring opportunities Exposure to modern data enginee