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Tier-1 brand, metro Bengaluru location, mid-level generalist title and 4+ years increases applicant competition.
Core data engineering skills are transferable, but financial regulatory and credit risk expectations increase sensitivity.
Multiple mandatory years of technical experience and regulatory/data governance expectations make shortlisting strict.
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Lead and deliver moderately complex technical initiatives and projects within credit risk technology domain, including coding, testing, deployment, and upgrades.
Design, develop, and optimize large-scale data engineering solutions and ETL/ELT pipelines using big data frameworks and cloud technologies for credit risk data.
Provide technical leadership, mentorship, and architectural guidance while collaborating with Credit Risk, Analytics, and Business stakeholders to create compliant, scalable solutions including Generative AI applications.
Minimum 4+ years of professional Software Engineering experience or equivalent.
4+ years hands-on experience building ETL/ELT pipelines on big-data platforms such as Apache Spark, Hadoop, Hive.
4+ years of experience in data engineering with PySpark/Python, Hadoop ecosystem tools, Hive and/or Scala.
Strong experience (4+ years) with RDBMS, SQL-based data modeling, plus 3+ years UNIX/Linux and Shell scripting experience.
Experience leading technical initiatives, mentoring engineers, and providing solution-level guidance (2+ years).
Prior work with credit risk, financial services, or regulated data environments, including knowledge of governance, security, auditability, and compliance.
Demonstrated capability in modern data platforms modernization (performance, scalability) and interest or experience applying Generative AI/AI/ML techniques within regulated domains.