Data Architect

Job Summary: Data Architect/Engineer (Google Cloud Platform) Key Responsibilities • Data Pipeline Development: Design, build, test, and maintain scalable data pipelines and ETL processes using Python and GCP services (e.g., Dataflow, BigQuery, Pub/Sub). • Data Integration & Modeling: Implement batch and real-time data integration workflows, optimize data models and architecture for performance and storage efficiency. • Collaboration & Support: Work with cross-functional teams to gather data requirements and support data analysts with curated datasets and tools. • System Reliability: Monitor, troubleshoot, and tune data systems for high availability, scalability, and disaster recovery. • DevOps Enablement: Build and manage CI/CD pipelines using GitHub and Terraform; ensure security compliance and operational readiness. Mandatory Skills & Qualifications • Technical Expertise: • Strong Python programming and Spark experience for data analytics. • Proficient in GCP services: GCS, Dataflow, Cloud Functions, Composer, Scheduler, Datastream, Pub/Sub, BigQuery, Dataproc. • Skilled in Apache Beam for batch and stream processing. • Experience with REST API ingestion, JSON messaging, and scripting (Shell, Perl). • Deep understanding of SQL, cloud-native databases, and data warehousing concepts. • Engineering & Migration: • Proven experience in migrating legacy systems to modern cloud-based architectures. • Familiarity with distributed computing frameworks and large-scale data handling. DevOps & Security: • CI/CD pipeline development with GitHub and Terraform. • Security integration in deployment workflows. Soft Skills: • Strong problem-solving and analytical abilities. • Excellent communication and teamwork skills.