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Tier-1 brand, generalist Data Engineer title, metro location, and broad skillset increase applicant competition.
Core data engineering skills are transferable, but Aladdin/financial analytics domain knowledge raises industry specificity.
Explicit 7+ years requirement plus domain experience and specific stack increases strictness.
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Design and own scalable data infrastructure and ETL pipelines optimized for Snowflake to support large-scale financial analytics datasets.
Partner with subject matter experts and modelers to translate requirements into production-grade, maintainable, and scalable data platform solutions.
Drive adoption of AI-assisted engineering tools to improve coding, testing, documentation speed and quality, ensuring adherence to data privacy and governance standards.
7+ years of professional Python programming experience with hands-on data engineering skills.
Experience building and maintaining ETL pipelines for large-scale datasets using industry-standard tools and distributed frameworks.
Strong understanding of database internals, data modeling, and data quality validation frameworks.
Work Experience Required: 7+ years; Location: Hybrid work model requiring at least 4 days per week onsite, 1 day remote (BlackRock office).
Experienced in financial or quantitative analytics data platforms with focus on scalability, production readiness, and operational SLAs.
Proficient in integrating AI-assisted development tools responsibly within secure, high compliance environments.
Operates effectively in a globally distributed engineering team collaborating closely with research and modeling professionals.