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Tier-1 brand, mid-level data engineer title, metro location, and broad pipeline skillset increase applicant competition.
Core data engineering skills transfer broadly, but portfolio management finance domain raises fit sensitivity.
Explicit 5+ years plus mandatory Snowflake, Python, SQL and cloud experience make screening strict.
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Lead design, development and optimization of scalable data pipelines and platforms for structured and unstructured data within fixed income portfolio management.
Own end-to-end data engineering solutions including ingestion, transformation, orchestration, storage, and service layers supporting analytics and AI use cases.
Provide technical leadership including mentoring, code reviews, architectural decisions, and driving best practices for reliability, scalability, and maintainability of data infrastructure.
Bachelor's or Master's degree in Computer Science, Engineering, or related field.
5+ years of relevant data engineering experience.
Strong expertise in Python, SQL and cloud data platforms like Snowflake.
Experience with data modeling, ETL/ELT design, pipeline optimization, data quality and monitoring practices for production environments.
Experienced data engineer with proven ability to architect and deliver enterprise-grade, large-scale data solutions in finance or related sectors.
Comfortable leading technical teams, mentoring junior staff and driving complex data initiatives end-to-end.
Technical proficiency in cloud platforms, data pipeline frameworks, CI/CD, and integrating data with AI/analytics applications.