Data Engineer, MASS

DRW 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.

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.

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. DRW is a place of high expectations, integrity, innovation and a willingness to challenge consensus.

**About the Role:
**

We are seeking Senior Data Engineers to join the Multi-Asset Systematic Strategies (MASS) trading team. One role will have a specific focus on equity products, markets and related data, whilst the other role will focus on futures products.

These roles will be responsible for onboarding, transforming, and managing equity or futures datasets. You will collaborate closely with traders, researchers, and quantitative developers to analyze equity or futures market structure and pricing dynamics to support delta-one trading strategies across global equities markets.

Key Responsibilities:

Asset class specific - Equities:

• Construction of point-in-time prices: process splits, dividends, spin-offs, mergers, symbol changes; compute adjusted close/total return and adjustment factors.

Asset class specific – Futures:

• Construction of curves and continuous series: build point-in-time, FND/LTD-aware continuous futures with explicit roll rules (volume/open-interest thresholds, calendar-based windows); generate term structures across maturities; compute roll yield/carry.

General: 

• Manage symbology and lifecycle management: maintain cross-exchange/vendor mappings (MIC + exchange symbols, Bloomberg, ISIN/RICs, etc.); manage instrument lifecycle events (listings, delistings, expiries, spec changes) to ensure consistency and point-in-time correctness.
• Develop point-in-time datasets for quantitative trading strategies, ensuring accurate historical data for analysis and model validation.
• Build, automate, and maintain resilient pipelines for cleaning, validating, and transforming batch and streaming data that feed into medallion architectures.
• Develop observability, monitoring, and alerting tools to provide complete visibility into pipeline reliability and performance.
• Optimize tiered data storage and elastic processing across on-prem, cloud, and hybrid environments to ensure scalable and cost-effective solutions.
• Enforce data governance, controls, and security standards to preserve confidentiality and operational integrity.

**
Qualifications:
**

• Over five years of demonstrated experience designing and implementing ingestion pipelines.
• Experience on a trading team and contributing to executing trading strategies.
• Equities – Deep expertise in equities market structure: multi-venue trading, NBBO, consolidated vs direct feeds, open/close auctions, halts; short-sale rules.
• Futures – Deep expertise in futures market structure: contract specs, exchange mechanics (trading sessions, calendars, time zones, price limits/halts), key dates, and roll mechanics.
• Proficient in analyzing and interpreting order book data and market dynamics.
• Familiarity with equities, equity futures, equity indices, and delta one trading is required.
• Experience processing real-time and batch financial market data.
• Proven ability to work in an agile, fast-paced environment and handle trading environment demands.
• Strong understanding of financial point-in-time and time-series data and analysis.
• Proven expertise in developing data quality control processes to detect gaps or inaccuracies.
• Experience with monitoring, observability, and alerting systems for data pipelines.
• Competent in both on-premise Linux systems and cloud platforms.
• Proficient in automated testing, CI/CD practices, and various Ops disciplines.
• Well-versed in compressed and optimized file formats such as Parquet and Iceberg.

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