Senior Data Platform Engineer

Chicago, IL (Hybrid - 4 Days Onsite)

We are partnering with a leading technology-driven quantitative trading and financial markets firm seeking a Senior Data Platform Engineer to join a team responsible for building and evolving large-scale data infrastructure. This role sits at the intersection of data engineering, distributed systems, and platform development, supporting high-volume, mission-critical data used across trading, research, and analytics functions.

What You'll Do

• Design, build, and maintain large-scale data platforms and storage systems supporting real-time and batch workloads.
• Develop and enhance data ingestion and processing pipelines using technologies such as Python, Java, Spark, Kafka, and related Big Data frameworks.
• Partner with software engineers, infrastructure teams, and data consumers to improve data accessibility, reliability, and performance.
• Support the evolution of modern data lake and table architectures, enabling scalable access to large datasets across the organization.
• Troubleshoot complex production issues, perform root-cause analysis, and drive long-term platform improvements.
• Contribute to data modeling, storage optimization, and capacity planning initiatives.
• Serve as a subject matter expert on distributed data systems and platform best practices.

What We're Looking For

• 5+ years of experience in Data Engineering, Data Platform Engineering, or related fields.
• Strong hands-on development experience with Python and SQL.
• Experience building and maintaining large-scale data pipelines and distributed data systems.
• Exposure to technologies such as Kafka, Spark, Hadoop/HDFS, Flink, Iceberg, Databricks, or similar platforms.
• Solid understanding of Linux/Unix environments and production troubleshooting.
• Experience working with cloud object storage platforms such as S3 or equivalent.
• Ability to read, understand, and collaborate on application code, with Java experience considered a strong plus.
• Demonstrated ownership mindset and ability to operate in fast-paced, highly technical environments.

Preferred Background

• Experience supporting large-scale data platforms serving engineering, analytics, or research organizations.
• Exposure to modern lakehouse architectures and large-volume data storage solutions.
• Experience with Kubernetes, Docker, monitoring, and observability tooling.
• Background in financial services, quantitative trading, large-scale technology companies, or other data-intensive environments is highly valued.

Why Consider This Opportunity?

• Join a highly technical team solving complex distributed systems and data challenges.
• Work on modern data platform initiatives involving next-generation storage and processing technologies.
• Influence critical infrastructure used across the business.
• Collaborative environment with significant ownership and visibility.