Data Engineer

Key ResponsibilitiesBuild, deploy, and maintain NLP pipelines to extract investment‑relevant events and signals from large volumes of unstructured text (including news, regulatory filings, and research reports).Design and implement scalable data models and analytical frameworks to support both quantitative and qualitative investment research.Leverage AWS services for storage, processing, orchestration, and operationalization of data workflows.Partner with investment analysts and data teams to define event taxonomies and ensure extracted outputs align with research and business requirements.Perform exploratory data analysis and feature engineering to improve downstream predictive models and alpha‑generation efforts.Uphold strong standards for code quality, reproducibility, documentation, and data integrity throughout the development lifecycle.Communicate findings, methodologies, and recommendations effectively to both technical and non‑technical stakeholders.Required Skills & Experience4+ years of hands‑on experience in data science.Proven expertise in extracting structured events from unstructured text using NLP techniques.Strong modelling capabilities across supervised and unsupervised learning methods.Advanced proficiency in Python, with solid SQL skills for data manipulation, extraction, and pipeline integration.Practical experience working with AWS or other major cloud platforms in data engineering or advanced analytics environments.Clear communication skills with the ability to translate technical work into actionable insights for cross‑functional teams.Demonstrated track record of working with large datasets and deploying data products in scalable production environments.