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Tier-1 brand, popular data engineer role, metro location, and broad technical requirements increase competition.
Technical skills are transferable but explicit financial-services experience requirement raises domain sensitivity.
Multiple explicit years and mandatory tech skill minimums create strict shortlisting filters.
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Develop and maintain scalable, efficient Python applications including Flask or FAST-based APIs.
Design and optimize databases using MongoDB and PostgreSQL, and build/deploy applications using Docker, Kubernetes, and OpenShift.
Set up and maintain CI/CD pipelines with Jenkins, SonarQube, and Git; perform root cause analysis on data/processes and handle unstructured datasets with scalable data processing solutions.
7-10 years overall software development experience.
At least 3 years hands-on experience with Python, Flask APIs, and MongoDB.
At least 2 years experience with Docker, Kubernetes, OpenShift, and in setting up CI/CD pipelines using Jenkins, SonarQube, and Git.
Minimum 2 years experience with Kafka or other message queuing systems; Bachelor's degree or equivalent; 2-4 years relevant Financial Services experience.
Intermediate level application developer comfortable managing complex data engineering tasks and infrastructure.
Experience working with scalable data pipelines and unstructured datasets, able to use container orchestration and CI/CD tools effectively.
Familiarity with AI/ML frameworks and Cloud services (AWS) preferred, indicating the ability to handle advanced analytics and cloud deployments.