Back
Tier‑1 brand and metro location, but senior GCP data specialization reduces applicant density to medium.
GCP data engineering skills are transferable across industries but require platform-specific experience.
Explicit 8–12 years plus mandatory GCP data stack and programming skills enforce high shortlisting strictness.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Design, build, and optimize data warehouses, lakes, and ETL/ELT workflows on Google Cloud Platform (GCP) to support analytics and AI initiatives.
Implement and manage data governance frameworks including lineage, metadata management, data quality, security, and compliance using GCP tools like Dataplex.
Collaborate with cross-functional teams to translate data requirements into scalable data engineering and architectural solutions using programming languages like Python, SQL, and Java.
8-12 years of relevant experience in data engineering and analytics.
Proficient in GCP data services: BigQuery, Dataflow, Pub/Sub, Dataproc, Dataplex, Cloud Storage, Data Catalog, Cloud Composer.
Strong programming skills in SQL and Python and/or Java.
Bachelor's degree in Engineering (B.Tech), MBA, M.Tech, or MCA explicitly required.
Experienced in end-to-end data pipeline design, data warehousing, and cloud-native data engineering on GCP.
Skilled in implementing data governance frameworks ensuring security, quality, and compliance within complex enterprise environments.
Familiarity or experience in AI/ML model support, including chatbot or AI assistant development, enhancing business process automation and intelligence.