Equities Data Engineer

<p><strong>DRW</strong> is a diversified trading firm with over 3 decades of experience bringing sophisticated technology and exceptional people together to operate in markets around the world. We value autonomy and the ability to quickly pivot to capture opportunities, so we operate using our own capital and trading at our own risk.</p> <p>Headquartered in Chicago with offices throughout the U.S., Canada, Europe, and Asia, we trade a variety of asset classes including Fixed Income, ETFs, Equities, FX, Commodities and Energy across all major global markets. We have also leveraged our expertise and technology to expand into three non-traditional strategies: real estate, venture capital and cryptoassets.</p> <p>We operate with respect, curiosity and open minds. The people who thrive here share our belief that it’s not just what we do that matters–it's how we do it. <strong>DRW</strong> is a place of high expectations, integrity, innovation and a willingness to challenge consensus.</p> <p class="p1">We are seeking an&nbsp;<strong>Equities Data Engineer</strong> to join the MASS (Multi-asset Systematic Strategies) trading team. In this role, you will be responsible for onboarding, transforming, and managing diverse financial datasets. You will collaborate closely with traders, researchers, and quantitative developers to analyze equity and futures data, identify alphas, and develop global delta-one trading strategies.</p> <p class="p1"><strong>Key Responsibilities:</strong></p> <ul class="ul1"> <li class="li1">Partner with traders, researchers, and analysts to deliver well-structured data that powers trading strategies, predictive models, and AI/ML applications.</li> <li class="li1">Build, automate, and maintain resilient pipelines for cleaning, validating, and transforming batch and streaming data that feed into medallion architectures.</li> <li class="li1">Develop observability, monitoring, and alerting tools to provide complete visibility into pipeline reliability and performance.</li> <li class="li1">Optimize tiered data storage and elastic processing across on-prem, cloud, and hybrid environments to ensure scalable and cost-effective solutions.</li> <li class="li1">Enforce data governance, controls, and security standards to preserve confidentiality and operational integrity.</li> <li class="li1">Implement data quality frameworks (validation, reconciliation, anomaly detection) to detect gaps, staleness, and corporate action/market data inconsistencies.</li> <li class="li1">Maintain point-in-time correctness across datasets used for research and live trading; ensure reproducibility of signals and backtests.</li> <li class="li1">Col