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Tier-1 brand, mid-level experience band, and metro location create high candidate competition.
Requires banking TLM experience and enterprise ETL/data-pipeline expertise, limiting cross-industry transferability.
Explicit 5–7 years plus numerous mandatory technical skills and banking domain requirements make shortlisting strict.
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Ensure accuracy, reliability, and performance of complex enterprise data pipelines, ETL processes, and data reconciliation workflows.
Develop and maintain automation frameworks and scripts using Python, Robot Framework, and AI/ML tools to improve testing efficiency and coverage.
Validate Apache Airflow workflows, REST APIs, and support deployment testing in Unix/Linux and OpenShift Container Platform environments with a focus on banking domain processes (Transaction Lifecycle Management and financial reconciliation).
5-7 years of professional experience in QA or related roles.
Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.
Strong expertise in Python (including Pandas, PySpark, NumPy), SQL, Robot Framework automation, REST API testing, and enterprise ETL tools (IBM DataStage, Informatica).
Mandatory banking domain knowledge, specifically Transaction Lifecycle Management (TLM) and financial reconciliation processes.
Experienced QA professional skilled in data testing, validation, and reconciliation in large-scale financial or banking systems.
Proficient in automating complex ETL pipeline validations and workflow orchestration within containerized/OpenShift environments.
Able to leverage AI-assisted tools like GitHub Copilot and Agentic AI frameworks to enhance testing workflows and productivity.