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Strong Tier-1 brand, metro location, and broad big-data skillset increase applicant competition.
Big-data engineering skills transfer across industries, though banking domain knowledge is preferred.
Explicit 8-10 years plus mandatory big-data stack skills and leadership make filters strict.
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Lead design and development of scalable big data architecture and pipelines ensuring high data quality, availability, and performance.
Drive technology evaluation, adoption, and optimization of big data tools like Hadoop, Spark, Kafka to improve processing capabilities.
Provide technical leadership and mentorship, while ensuring compliance with data governance and security best practices.
8-10 years of software development experience focused on handling large-scale data volumes.
Bachelor's or Master’s degree in Computer Science, IT, or related field.
Strong programming skills in Java, Scala, or Python and experience with big data technologies including Hadoop, Spark, Kafka, Python, PySpark.
Experience designing and implementing scalable big data architectures and complex data transformation processes.
Experienced leader capable of managing big data architecture strategy and cross-functional technical collaborations.
Deep technical expertise in big data ecosystems and hands-on experience with data pipeline development and optimization.
Proven ability to innovate on data processing frameworks and implement data governance in complex environments, preferably with exposure to financial services domain.