Back
Mid-level GCP data engineer in Bangalore with broad required stack and popular title increases competition.
Strong GCP-specific data engineering and FinOps requirements reduce cross-industry portability.
Explicit 5-8 years requirement, mandatory GCP experience, and extensive GCP stack make filters stringent.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Design, implement, and optimize enterprise-scale data platforms and scalable batch and streaming data pipelines on Google Cloud Platform (GCP).
Lead cloud cost optimization initiatives including workload right-sizing, cost management, and FinOps practices to reduce cloud spend and improve resource utilization.
Define and enforce governance standards for resource tagging, cost allocation, and cloud governance, collaborating with multiple stakeholders including engineering, architecture, finance, and business teams.
5-8 years of experience in Data Engineering, Cloud Engineering, or Cloud Architecture.
Minimum 3+ years of hands-on experience with Google Cloud Platform (GCP).
Strong hands-on experience with key GCP Data Engineering and Compute services (e.g., BigQuery, Dataproc, Dataflow, Pub/Sub, GKE, Compute Engine).
Work Location: Hybrid role requiring minimum two days per week in assigned TransUnion office location.
Proven track record in enterprise-scale cloud-native data platform design and optimization focusing on GCP ecosystem.
Experience driving measurable cloud cost savings and operational efficiencies via FinOps and workload tuning in data engineering contexts.
Strong collaboration skills with cross-functional teams including technical leadership, finance, and business stakeholders to provide technical guidance and cost-benefit analysis.