GCP Data Engineer

Technology->GCP, SQL, BigQuery, Cloud Storage, Pub/Sub, Dataflow, Cloud Monitoring

Key Responsibilities:

• Lead end-to-end solution design and implementation on GCP, ensuring scalability, reliability, and cost efficiency.
• Translate business requirements into technical architecture, data models, and implementation plans.
• Design, optimize, and maintain complex SQL queries, schemas, and performance tuning strategies for large datasets.
• Establish and enforce engineering standards for cloud architecture, security, monitoring, and operational readiness.
• Drive technical reviews, architecture discussions, and decision-making across teams and stakeholders.
• Mentor engineers through code reviews, design guidance, and best practices for cloud and data development.
• Troubleshoot production issues, perform root-cause analysis, and implement preventive improvements.
• Collaborate with cross-functional teams to deliver milestones on time with high quality and clear documentation. Minimum Qualifications:
• 7–9 years of overall experience in technology delivery with strong ownership of system design and implementation.
• Bachelor's or Master's degree in BTECH, MTECH, MCA, or MSC (or equivalent relevant education).
• Strong hands-on experience with GCP services and cloud-based solution delivery.
• Strong proficiency in SQL, including query optimization, indexing concepts, and handling large-scale datasets.
• Experience leading technical discussions, guiding implementation, and ensuring engineering quality. Preferred Qualifications:
• Experience designing cloud architectures with clear patterns for scalability, resilience, and security on GCP.
• Strong understanding of data warehousing and analytics patterns using GCP-native services.
• Exposure to CI/CD practices and automated deployments for cloud workloads.
• Proven ability to lead teams through ambiguity, manage technical risks, and drive delivery outcomes.
• Experience collaborating with stakeholders to define KPIs, SLAs, and operational metrics for production systems.