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Tier-1 brand, mid-level generalist title, metro location, broad skillset increases applicant competition.
Requires financial audit experience and data-policy compliance, limiting cross-industry transferability.
Mandatory 5+ years in financial industry plus specific techs and security requirements raises filter strictness.
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Own the full-stack development and operationalization of internal audit software tools, including front end, data pipelines, and AI/ML model integration.
Build and maintain scalable, production-grade data pipelines and AI workflows that enhance audit efficiency and reliability.
Ensure system stability and security through CI/CD automation, monitoring, and collaboration across global teams.
5+ years of experience with cross-regional collaboration in the financial industry.
Bachelor’s or Master’s degree in System Engineering, Computer Science, Data Engineering, Information Systems, or related field.
Proficiency in Python, SQL, and modern programming languages; experience with data pipeline tools, REST APIs, ETL frameworks like Snowflakes.
Strong Linux, network, cyber engineering knowledge, and familiarity with ML model deployment and UI/UX development.
Experienced in pragmatic system architecture design balancing advanced technologies with ROI-driven solutions.
Proven ability to build reusable, modular software aligned with software development best practices and documentation.
A collaborative engineer capable of working effectively across time zones with global teams and supporting integration within complex financial technology environments.