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Tier-1 employer plus common mid-level data engineer title and 5+ years requirement increases candidate competition.
Core data engineering skills are transferable, though banking compliance and platform specifics increase domain preference.
Explicit 5+ years plus mandatory GCP, ETL, PySpark, and data platform skills make filters strict.
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Lead complex, companywide data engineering and cloud platform technology initiatives with broad impact.
Architect and build scalable data pipelines and enterprise-scale ETL/ELT solutions using GCP and related cloud-native technologies.
Provide technical leadership, mentor engineering teams, and drive best practices in data integration, transformation, and orchestration.
Minimum 5+ years of software engineering experience or equivalent through work, training, military experience, or education.
Experience with Google Cloud Platform data engineering services and ETL tools (e.g., Ab Initio, Informatica, DataStage, Talend, SSIS) is required.
Education preferred: B.E./B.Tech. or M.E./M.Tech. in Computer Science, IT, ECE, or related discipline with strong academic record.
Notice period: Not explicitly mentioned in the JD.
Demonstrated ability to lead technical direction and design large-scale cloud data engineering solutions, particularly on GCP.
Experienced in mentoring and leading software engineering teams with a focus on data engineering, ETL, and cloud modernization.
Strong knowledge of data governance, security, data modeling, and operational excellence in enterprise environments.