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Tier-1 brand, mid-level metro data engineer role with broad GCP and ETL requirements.
GCP, ETL, PySpark skills transfer across industries, though banking compliance adds moderate bias.
Explicit 5+ years plus mandatory GCP, ETL, PySpark and leadership skills indicate stringent filtering.
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Lead design, development, and support of enterprise-scale data engineering and ETL/ELT solutions on Google Cloud Platform (GCP).
Drive technical direction, mentor engineering teams, and establish best practices for data integration, transformation, and cloud modernization initiatives.
Collaborate cross-functionally to translate requirements into scalable, secure, and high-performance data platforms and pipelines with focus on performance tuning and operational excellence.
5+ years of Software Engineering experience or equivalent through work experience, training, military experience, or education.
B.E./B.Tech. or M.E./M.Tech. in Computer Science, Information Technology, ECE, or related discipline with strong academic record.
Hands-on experience with ETL tools such as Ab Initio, Informatica, DataStage, Talend, SSIS, or similar and strong expertise in Google Cloud Platform data engineering services.
Experience with Agile methodologies, CI/CD practices, data governance frameworks, and leading design reviews or mentoring engineering teams.
Proven technical leadership in cloud-native, large-scale data engineering projects with focus on GCP and modern data platforms.
Strong background in building scalable data lakes, lakehouses, data warehouses using Python, PySpark, SQL, and ETL tools.
Experience collaborating with cross-functional teams and driving cloud modernization and data governance in enterprise environments.