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Global brand plus broad cross-cloud and data skillset increases competition.
Core data engineering skills are transferable, though enterprise financial-data context adds moderate domain specificity.
Explicit 8+ years plus mandatory cloud, Python, SQL, Terraform, and BigQuery requirements increase strictness.
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Architect, design, and develop scalable cloud-based data applications and pipelines within an Agile team.
Lead and implement traditional AI and GenAI initiatives to enhance development speed and code quality.
Manage complex architectural problems, optimize existing solutions, and ensure system reliability through troubleshooting and debugging.
8+ years of hands-on experience in Software Engineering, Data Engineering, or Data Science.
Bachelor’s degree in Computer Science, Engineering, or related field (or equivalent work experience).
Expert-level skills in Python, SQL, and PostgreSQL.
Strong experience with Cloud platforms (AWS preferred, Azure or GCP), Infrastructure as Code (Terraform), and Message Broker Systems.
Experienced technical lead capable of driving architecture and best practices for enterprise-scale, cloud-native data systems.
Deep domain expertise in data processing pipelines, event-driven architecture, and cloud infrastructure reliability.
Proven ability to integrate AI and GenAI tools into development workflows to accelerate delivery and improve code quality.