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Mid-level data engineer, metro location, broad required skills, and popular role increase competition.
Role requires front-office finance and quant workflows experience, reducing transferability across industries.
Multiple mandatory technical skills, 5+ years experience and finance domain knowledge make filters strict.
Design, build, and maintain scalable data platforms, pipelines, and services to deliver high-quality investment-enabling data across the firm.
Collaborate closely with Front Office Quantitative Researchers and Data & Analytics Engineering teams to translate data requirements into robust, production-ready solutions.
Own full solution lifecycle including design, implementation, testing, deployment, and first-line production support in a cloud-native environment.
5+ years of professional experience in data or software engineering, preferably in financial services or buy-side/sell-side environment.
Strong expertise in Python with solid software engineering practices (version control, testing, CI/CD).
Experience with cloud-native data pipelines and platforms, preferably AWS; familiarity with Docker and containerized deployments.
Proficiency in Snowflake and NoSQL databases (MongoDB); good understanding of financial markets and instruments.
Demonstrates deep integration with quantitative research teams and ability to translate complex business problems into scalable data solutions.
Experienced in operating and supporting data platforms in fast-paced, production-critical financial environments with ownership over end-to-end solution lifecycle.
Capable of working independently and cross-functionally, with strong communication and stakeholder management skills focused on front office investment workflows.