Back
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Tier-1 brand, mid-level generalist title, metro location, and broad Big Data skill requirements drive high candidate competition.
Strong Big Data engineering skills are transferable, but banking domain preference creates medium background sensitivity.
Explicit 6–9 years plus mandatory Java, Spark, Azure, and Kubernetes skills enforce high shortlisting strictness.
Design, develop, test, and optimize components/modules in the Trade Open Platform (TOP) using Spark, Java (1.8), Hive, and big-data technologies within a datalake architecture.
Contribute to design, development, deployment of new features & components, including REST API evolution, on Azure public cloud using CD/CI practices across development, UAT, and production environments.
Participate in Agile@Scale ceremonies (PI Planning, Sprint planning), manage backlog in Jira, and organize technical training sessions for stakeholders on core platform and related technologies.
6-9 years of IT industry experience, preferably in banking domain.
Expertise in Java 1.8 (API building, threading, collections, streams, dependency injection), Big Data technologies (Spark, Oozie, Hive), and Azure (AKS, CLI, Event, Key Vault).
Experience developing REST APIs and managing tools like GIT/Bitbucket, Jenkins, NPM, Docker/Kubernetes, Jira, Sonar.
Knowledge of Agile practices and Agile@Scale methodology. Work Experience Required: 6-9 years. Notice period: Not explicitly mentioned in the JD.
Experienced in digital transformation initiatives in banking or financial services environments.
Skilled at balancing development, deployment, performance tuning, and operational process adherence in cloud-based big data platforms.
Comfortable working within Agile@Scale frameworks and capable of leading technical training and collaboration across teams.