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Data Operations Engineer

Optiver
🇺🇸ChicagoMediorFull-time$140k–$200kPosted October 7, 2026

About the Role

At Optiver, technology and data are at the core of every trading decision we make. As a leading global market maker, we rely on accurate, reliable, and scalable data platforms to power our trading, research, and analytics systems in some of the world's fastest financial markets.

As a Data Operations Engineer, you'll join our Global Data Engineering team in Chicago, partnering closely with traders, researchers, and engineers to ensure our data platform operates reliably at scale. Combining software engineering with operational ownership, you'll troubleshoot production issues, onboard new datasets, improve platform reliability, and build the systems that keep our trading teams supplied with high-quality data every day.

Key responsibilities include:

  • Serving as the primary point of contact for traders, researchers, and engineers on data platform issues and operational support
  • Investigating and resolving data quality, freshness, and availability issues across business-critical datasets
  • Monitoring data ingestion pipelines, scheduled workflows, and real-time market data feeds, responding rapidly to alerts and minimizing production impact
  • Partnering directly with external data vendors to resolve upstream issues, manage specification changes, and ensure timely delivery of accurate datasets
  • Integrating and operationalizing new datasets, including schema mapping, normalization, historical backfills, and metadata management
  • Designing, building, and maintaining reliable, scalable ETL/ELT pipelines supporting both real-time trading systems and research platforms
  • Developing automated data quality validation, monitoring, and anomaly detection frameworks
  • Building and maintaining high-performance APIs that expose market and reference data to trading, research, and analytics platforms
  • Contributing to the ongoing evolution of Optiver's global data platform, improving reliability, observability, and operational excellence

Responsibilities

  • Serve as the primary point of contact for traders, researchers, and engineers on data platform issues and operational support
  • Investigate and resolve data quality, freshness, and availability issues across business-critical datasets
  • Monitor data ingestion pipelines, scheduled workflows, and real-time market data feeds, responding rapidly to alerts and minimizing production impact
  • Partner directly with external data vendors to resolve upstream issues, manage specification changes, and ensure timely delivery of accurate datasets
  • Communicate clearly during production incidents, providing timely updates and driving issues through to resolution
  • Integrate and operationalize new datasets, including schema mapping, normalization, historical backfills, and metadata management
  • Design, build, and maintain reliable, scalable ETL/ELT pipelines supporting both real-time trading systems and research platforms
  • Develop automated data quality validation, monitoring, and anomaly detection frameworks to proactively identify issues
  • Model and normalize complex financial datasets to ensure they are accurate, consistent, and production-ready
  • Build and maintain high-performance APIs that expose market and reference data to trading, research, and analytics platforms
  • Partner closely with traders, researchers, and engineering teams to understand evolving data requirements and deliver scalable solutions
  • Contribute to the ongoing evolution of Optiver's global data platform, improving reliability, observability, and operational excellence

Requirements

  • 3+ years of experience as a Data Engineer, Data Operations Engineer, Software Engineer, Site Reliability Engineer, or similar role in a high-performance or mission-critical environment
  • Experience building and maintaining scalable data pipelines, APIs, and data processing systems
  • Strong understanding of data modeling, normalization, and data quality best practices
  • Experience with modern lakehouse technologies such as Delta Lake, Databricks, or cloud-based data platforms is preferred
  • Exposure to real-time and historical financial market data (such as equities, ETFs, fixed income, or credit) is advantageous
  • Strong operational mindset with a passion for ownership, troubleshooting, automation, and continuous improvement
  • Excellent communication and collaboration skills, with the ability to partner effectively with traders, researchers, engineering teams, and external data vendors
  • Strong Python programming skills, including experience with libraries such as Pandas, PyArrow, and Spark
  • Legal authorization to work in the U.S. is required

What You'll Get

  • $140k–$200k base salary
  • The opportunity to work alongside best-in-class professionals from over 40 different countries
  • 401(k) matching up to 50%
  • Comprehensive medical, dental, vision, disability, life, and mental health coverage
  • 25 paid vacation days alongside market holidays
  • Extensive office perks, including breakfast, lunch and snacks, regular social events, clubs, sporting leagues, and more