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Tier-1 brand, mid-level data role with broad tech stack and metro appeal increases qualified applicant competition.
Core data engineering skills are transferable, though finance KYC/risk experience moderately increases background sensitivity.
Mandatory 5+ years plus specific enterprise data, cloud, and tooling experience increases shortlisting strictness.
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Lead development and delivery of secure, scalable data-intensive applications for global KYC and risk assessment platforms.
Define architecture, best practices, and reusable software frameworks used across multiple engineering teams.
Advise cross-functional teams on technology and drive adoption of advanced development and automation practices.
5+ years of applied software engineering experience with formal training or certification.
Expertise in Python and/or Java programming languages.
Experience in large-scale data processing, microservices, API design, and relevant tools like Kafka, Redis, Airflow, and observability tools.
Practical cloud-native experience in AWS, Azure, or GCP.
Experienced in enterprise-scale system design, development, testing, and operational stability for data platforms.
Strong background in data engineering and advanced software development processes, including cloud and AI/ML disciplines.
Comfortable communicating technology strategy and status effectively to senior leaders and multiple teams.