Equities Data Engineer

Overview In this role you will onboard, transform, and manage diverse financial datasets to support trading strategies and AI/ML applications. You will partner with traders and researchers to deliver reliable data for alpha discovery and delta-one trading. You’ll build and maintain resilient data pipelines across on-prem and cloud environments, with governance and quality controls to ensure reproducibility and performance. This is a fast-paced, collaborative role at a diversified trading firm focused on executing complex data-driven strategies at scale. Compensation / Benefitsgroup medical, pharmacy, dental and vision insurance401k with discretionary employer matchshort and long-term disabilitylife and AD&D insurancehealth savings accountsflexible spending accounts ResponsibilitiesPartner with traders, researchers, and analysts to deliver well-structured data for trading strategies, predictive models, and AI/ML applications.Build, automate, and maintain data pipelines for cleaning, validating, and transforming batch and streaming data.Develop observability, monitoring, and alerting tools for pipeline reliability and performance.Optimize data storage and processing across on-prem, cloud, and hybrid environments for scalability and cost-effectiveness.Enforce data governance, controls, and security standards.Implement data quality frameworks to detect gaps, staleness, and data inconsistencies.Maintain point-in-time correctness and reproducibility of signals and backtests.Collaborate with platform/infrastructure teams to productionize pipelines and meet latency/availability requirements. Key requirementsFive+ years in designing ingestion pipelines.Familiarity with equities, indices, futures, or delta-one data preferred.Experience processing real-time and batch market data.Ability to work in an agile, fast-paced trading environment.Strong understanding of time-series and point-in-time data analysis.Experience with data quality control processes.Experience with monitoring, observability, and alerting systems for data pipelines.Proficiency with on-prem Linux and cloud platforms.Experience with automated testing, CI/CD, and MLOps.Familiarity with Parquet and Iceberg formats.collaborationadaptabilityattention to detaildata pipelinesbatch and streaming datadata governance and security