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Remote role with generalist developer title but quantitative data engineering specialization moderates applicant competition.
Core data engineering and ML skills are transferable, but financial domain knowledge increases hiring sensitivity.
Senior-level role requiring specific cloud, big-data and ML tooling makes shortlisting highly stringent.
Lead design and development of quantitative data engineering models and algorithms using Python on AWS cloud infrastructure.
Develop and maintain robust data processing pipelines and ensure data quality, scalability, and efficiency.
Collaborate with cross-functional teams to deliver customer-facing quantitative solutions and document design and results for transparency.
Proficiency in Python and experience with cloud computing platforms, specifically AWS.
Strong background in data engineering and quantitative analysis, including statistical modeling and machine learning.
Experience with big data technologies such as Apache Spark, Kafka, or Hadoop and data visualization tools.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced in building scalable, cloud-native quantitative data engineering solutions in a financial or data analytics environment.
Comfortable leading model development and collaborating closely with data scientists and business stakeholders.
Demonstrates strong technical abilities in software development, performance optimization, and continuous learning in relevant quantitative technologies.