Job Description

Quant Dev / Data Engineer – Quantitative Investments

As a Data Engineer, you will design, build, and maintain high-performance data systems that support the full lifecycle of research and trading:

• Design, implement, and evolve robust data processing and storage infrastructure
• Build software libraries and enriched datasets that unlock advanced research and LLM-driven capabilities
• Automate the scheduling, orchestration, and deployment of research projects into live trading systems
• Ensure the highest standards of data quality through automated checks and ad-hoc analysis
• Develop dashboards and monitoring tools that provide visibility across the entire data lifecycle
• Build and maintain scalable ETL and ELT pipelines to onboard and transform diverse data sources
• Collaborate closely with quantitative researchers to accelerate experimentation and productionization

Required Qualifications

• 2+ years of experience in Data Engineering, ideally within a data-driven, multidisciplinary environment
• Strong proficiency in Python and SQL
• Excellent written and verbal communication skills
• Exceptional attention to detail in both data analysis and data engineering
• Strong sense of ownership and accountability for projects end-to-end
• Ability to quickly learn and understand complex business and research domains
• Proven ability to prioritize effectively and focus on high-impact work

Preferred Qualifications

• Experience with distributed or cluster computing frameworks (e.g., Spark, Dask )
• Experience with workflow orchestration tools (e.g., Airflow, Dagster, Prefect )
• Familiarity with cloud-based data warehouses and platforms (e.g., Databricks, Snowflake, Redshift )
• Prior experience in a quantitative trading firm, hedge fund, or working with time-series, market, or alternative data
• Experience supporting machine learning, LLM, or NLP data pipelines and workflows

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