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Tier-1 bank, mid-level Data Engineer title, and metro recruiting make applicant competition high.
Core data engineering skills are transferable, but financial treasury/ALM domain needs raise specificity moderately.
Multiple mandatory technical skills and 4+ years experience make shortlisting strict and selective.
Design, develop, and optimize scalable, metadata-driven data engineering frameworks and pipelines supporting financial risk processes in Corporate Treasury.
Lead technical initiatives including Data Center exit migrations, DPC onboarding, and enterprise modernization with focus on big data pipelines, cloud-native engineering, and data quality.
Develop and maintain APIs, automation scripts, and orchestration workflows to ensure reliable data ingestion, validation, and delivery across cloud and on-prem environments.
4+ years of Software Engineering experience or equivalent (work experience, training, military experience, education).
Proficiency in Python, SQL, and bash scripting.
Experience with big data technologies such as Apache Spark, Hive, Hadoop, and orchestration tools like Autosys or Airflow.
Work Experience Required: 4+ years of relevant software engineering experience.
Strong expertise in designing and maintaining complex distributed data pipelines and lakehouse architectures using Spark, Iceberg, and similar technologies.
Experience in financial domain data engineering, particularly related to risk, treasury, or Asset and Liability Management (ALM).
Demonstrated ability to lead moderately complex projects and resolve technical issues independently, including building automated data quality and observability frameworks.