Data Engineer, Associate - Aladdin Financial Engineering
BlackRockNew York, NYPosted 2 April 2026
Job Description
About this role
Join a diverse and collaborative team of over 300 modelers and technologists in Aladdin Financial Engineering (AFE) within BlackRock Solutions, the business responsible for the research and development of Aladdin’s financial models. This group is also accountable for analytics production, enhancing the infrastructure platform and delivering analytics content to portfolio and risk management professionals (both within BlackRock and across the Aladdin client community). The models developed and supported by AFE span a wide array of financial products covering equities, fixed income, commodities, derivatives, and private markets. AFE provides investment insights that range from an analysis of cash flows on a single bond, to the overall financial risk associated with an entire portfolio, balance sheet, or enterprise.
Role Description:
We are looking for a person to join the Advanced Data Analytics team within AFE Single Security. Advanced Data Analytics is a team of Quantitative Data Specialists, focused on delivering Research & Derived Data, Governance and Research Platform. The team leverages data, cloud, and emerging technologies to deliver research and production data/data solutions, for core analytics and investment teams, in the Single Security space. The team uses various statistical/mathematical methodologies to derive insights and generate content to help develop predictive models, clustering, and classification solutions and enable Governance. The team works on Mortgages, Structured Products, Credit Products, and Private Markets.
We are looking for a person to work on our Structured Product space as well as focus on public structured products. The individual will contribute as SME on structured products. The person will leverage Big Data technologies, Data platforms like Snowflake, Databricks to build out comprehensive analytics offering backed by enhanced data as well as leverage AI for efficiency and agentic automation. The person will partner with Investment teams and clients to help generate Investment Intelligence.
Experience
Strong analytical and problem-solving skills
Excellent communication t abilities.
Experience in Scala & Functional Programming
Knowledge of ETL, data curation and analytical jobs
Experience leveraging distributed computing framework with Spark
Basic knowledge of financial instruments like Bonds, Derivatives etc.
Basic knowledge of statistical methodologies
Knowledge and Experience of working with large enterprise databases like Snowflake, Cassandra
Experience in cloud managed services like Dataproc, Databricks is a plus
Experience in Python is a plus
Qualifications
Bachelor’s/master's in computer science with a minor in Math, Econ, or related field
3 years of relevant experience

For New York, NY Only the salary range for this position is USD$137,500.00 - USD$170,000.00 . Additionally, employees are eligible for an annual discretionary bonus, and benefits including healthcare, leave benefits, and retirement benefits. BlackRock operates a pay-for-performance compensation philosophy and your total compensation may vary based on role, location, and firm, department and individual performance.

Our benefits
To help you stay energized, engaged and inspired, we offer a wide range of benefits including a strong retirement plan, tuition reimbursement, comprehensive healthcare, support for working parents and Flexible Time Off (FTO) so you can relax, recharge and be there for the people you care about.
Our hybrid work model
BlackRock’s hybrid work model is designed to enable a culture of collaboration and apprenticeship that enriches the experience of our employees, while supporting flexibility for all. Employees are currently required to work at least 4 days in the office per week, with the flexibility to work from home 1 day a week. Some business groups may require more time in the office due to their roles and responsibilities. We remain focused on inc ... (truncated, view full listing at source)
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