Google Cloud Platform Data Engineer

Infosys; Bengaluru; On-site; INR 1,800,000 - 3,000,000; Full time

Job summary

Infosys in Bengaluru is seeking a GCP Data Engineer to design and implement scalable cloud data solutions using GCP services such as BigQuery, Pub/Sub, and Dataflow. You will translate business requirements into data models and architectures.

You will lead end-to-end projects, mentor engineers, optimize SQL queries, and ensure security, reliability, and cost efficiency. The role demands 7–9 years of delivery experience and a strong background in cloud architectures.

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.

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.

Skills

GCP

SQL

BigQuery

Cloud Storage

Pub/Sub

Dataflow

Cloud Monitoring

Education

B.Tech / M.Tech / MCA / MSc

Tools

CI/CD

Job description

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

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.

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.