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Tier-1 brand, mid-level generalist data role, and metro location create high applicant competition.
Banking and ETL platform preference increases domain specificity, while Python/Big Data skills remain moderately transferable.
Explicit 4-8 years plus mandatory Python/ETL and data platform experience drives high shortlisting strictness.
Lead design, development, and maintenance of enterprise-scale automation frameworks using Python, focusing on testing, validation, and operational automation for data-intensive applications.
Support ETL and large-volume data processing environments by performing data analysis, reconciliation, and quality validation, including working with Ab Initio and Big Data platforms.
Collaborate closely with Business Users, SMEs, Developers, and Scrum teams to ensure successful delivery of enterprise solutions and drive quality engineering practices in Banking and Financial Services contexts.
4-8 years of strong hands-on experience in Python scripting and automation framework development.
Strong expertise in ETL testing and data validation with SQL and Oracle database experience.
Proficient in Unix/Linux including shell scripting and experience in batch-processing/distributed environments.
Work Experience Required: 4-8 years relevant experience in Python automation, ETL testing, and data engineering.
Experienced in large-scale data processing and validation within Banking and Financial Services domain, preferably with high-volume transaction systems.
Comfortable engaging with Agile teams and stakeholders including Business Users, SMEs, Product Owners, using tools like JIRA and Confluence.
Skilled at developing reusable automation utilities and frameworks, with troubleshooting and analytical strengths targeting enterprise data platforms such as Ab Initio and Big Data ecosystems.