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Tier-1 employer, mid-level generalist big-data role, and metro location increase competition.
Requires financial-services experience and specialized Big Data skills, limiting cross-industry transferability.
Explicit 4–8 years, financial-services experience, and mandatory PySpark/Java big-data skills increase filtering strictness.
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Design, develop, and optimize scalable ETL data pipelines using PySpark for large datasets.
Write clean, efficient code primarily in Python (PySpark) and Java, involved throughout the full software development lifecycle.
Collaborate with cross-functional teams to understand data requirements, ensure data quality, and troubleshoot Spark and big data technologies.
4-8 years of relevant experience in the Financial Services industry in Applications Development.
Proficiency in Core Java, Python (PySpark), and knowledge of big data technologies like Apache Spark, Hadoop, Hive, and Sqoop.
Bachelor’s degree or equivalent experience required.
Familiarity with Linux OS, shell scripting, and basic SQL; experience with cloud platforms (AWS, Azure, or GCP) is expected.
Experienced in intermediate applications development within Financial Services with strong programming skills in Java and PySpark.
Comfortable working in Agile/Scrum environments handling end-to-end software development and collaborating with cross-functional teams.
Skilled in performance optimization and troubleshooting of big data pipeline processing and maintaining data integrity.