Back
Medium — strong BlackRock brand but niche Scala+quant finance data engineering reduces generalist applicant pool.
High — requires specialized quantitative finance domain knowledge and Scala/Spark data engineering expertise.
High — explicit 7+ years plus mandatory Scala, Spark, cloud data platform and finance domain requirements.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Develop and deliver comprehensive analytics data solutions and APIs using Big Data technologies and AI for portfolio risk and investment analytics.
Serve as subject matter expert on Portfolio Risk Analytics data to support investment teams and clients by generating actionable investment intelligence.
Leverage platforms such as Snowflake, Databricks, and distributed computing frameworks like Spark to build scalable, production-grade data workflows and analytics pipelines.
7+ years of experience in Data Engineering, Quantitative Analytics, or Financial Technology environments.
Strong programming skills in Scala with solid understanding of Functional Programming concepts.
Experience with Spark, ETL development, data curation, and enterprise/cloud data platforms such as Snowflake, Cassandra, Databricks, or Dataproc.
Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, Economics, Statistics, or related quantitative field.
Experienced in building scalable big data analytics products within a financial or quantitative environment focusing on portfolio risk and investment analytics.
Comfortable working with complex financial instruments data sets including bonds, derivatives, and credit products.
Proficient in leveraging AI/ML workflows and data governance frameworks to enhance analytics efficiency and automation in production environments.