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Tier-1 brand, metro location, mid-level generalist Big Data role with broad skills.
Banking-specific experience is requested, reducing cross-industry transferability.
Explicit 4–8 years and mandatory PySpark/Big Data/Java skills enforce stringent screening.
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Design, develop, and maintain scalable ETL data pipelines using PySpark and Java, handling large datasets.
Write clean and efficient code primarily in Python (PySpark) and Java, employing frameworks like Spring Boot.
Engage in full software development lifecycle including requirements analysis, testing, deployment, and operations within Agile/Scrum teams.
4-8 years of relevant experience in Applications Development, preferably in Financial Services industry.
Proficient in Core Java, Python (PySpark), and big data technologies including Apache Spark, Hadoop ecosystem components (Hive, Sqoop).
Bachelor’s degree or equivalent experience.
Knowledge of Linux OS with shell scripting and basic SQL skills required.
Experience working in cross-functional teams with developers, data engineers, analysts, and business stakeholders, indicating strong collaboration in complex environments.
Comfortable troubleshooting and optimizing Spark applications and big data processing pipelines under pressure and changing requirements.
Familiarity with cloud platforms (AWS, Azure, GCP), version control (Git), and understanding of DevOps/CI-CD pipelines signals readiness for modern development environments.