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Tier-1 brand and metro location increase competition, but senior niche skillset moderates applicant density.
Big Data and ML engineering skills are transferable, though financial services experience preference increases specificity.
Mandatory 12+ years plus specific Big Data, ML pipeline, cloud and NoSQL skills enforce strict screening.
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Lead application systems analysis and programming activities, focusing on establishing and implementing new or revised application systems.
Partner with multiple management teams to integrate functions, identify enhancements, and deploy new products and process improvements.
Provide expertise on application design ensuring adherence to architecture blueprints and oversee standards for coding, testing, debugging, and implementation.
12+ years of relevant experience in an Engineering role within Financial Services or a large complex/global environment.
3+ years experience with Big Data technologies including Apache Spark, Hive, Hadoop, and Storm.
Strong programming skills in Python, including experience with data manipulation and AI/ML pipeline scripting.
Bachelor's degree or equivalent experience; Master's degree preferred.
Experienced in designing and implementing large-scale data solutions for AI/ML applications using Big Data and cloud technologies.
Capable of working independently and managing multiple project components, with ability to operate effectively in a matrix environment with virtual teams.
Strong problem-solving skills with ability to assess risk and ensure compliance with legal and policy standards in a financial institution context.