Data Engineer - ETF Platform

Location: Downers Grove, IL (4 days in office, 1 day remote)

Work Authorization Notice

This role does not offer visa sponsorship now or in the future. Candidates must be authorized to work in the United States on a permanent basis without sponsorship.

Role Overview

We are seeking a Data Engineer to design, build, and support data‑driven platforms and applications that power portfolio construction, trading, analytics, and operational workflows across Equities, Fixed Income, and Alternatives.

This role sits at the intersection of data engineering, application development, and distributed systems, partnering closely with portfolio managers, quantitative researchers, and business teams. You will help modernize platform architecture, improve data pipelines, and raise engineering standards across a production‑critical investment technology environment.

You will operate in a fast‑paced setting that values hands‑on ownership, strong collaboration across global teams, and a focus on building resilient, production‑grade systems that reduce operational risk.

Key Responsibilities

• Drive AI‑accelerated engineering practices, including daily use of tools such as GitHub Copilot, Claude, ChatGPT, and AWS Bedrock for coding, testing, documentation, and prototyping, with clear review standards for AI‑generated code
• Design, build, and maintain data engineering workflows and platform services supporting model delivery and analytics ecosystems
• Develop platform components responsible for data ingestion, transformation, validation, and routing across internal and external systems
• Build Python‑based services, APIs, and microservices supporting portfolio analytics, optimization workflows, and data pipelines
• Design and optimize SQL‑based data processing (PostgreSQL, SQL Server, Snowflake), including complex queries, performance tuning, and large‑scale ETL workflows
• Implement and support distributed, event‑driven architectures, including Kafka and asynchronous processing patterns
• Develop and maintain cloud‑native applications on AWS, including Lambda, S3, ECS/EKS, Step Functions, and Aurora
• Design and operate CI/CD pipelines to ensure reliable, repeatable deployments
• Ensure data quality, auditability, and observability through logging, monitoring, lineage tracking, and validation frameworks
• Collaborate closely with investment and analytics teams to translate portfolio construction, risk, and analytical requirements into scalable technical solutions
• Continuously improve platform reliability and performance through modern engineering practices, testing, and automation
• Participate in production support and on‑call rotation as needed

Experience & Qualifications

• Bachelor's degree in Computer Science, Engineering, Data Science, or a related field
• 3 years of hands‑on experience in software engineering or data engineering (financial services or asset management experience preferred)
• 3 years of experience with Python, including data processing, APIs, or service‑based architectures
• 3 years of experience with SQL (PostgreSQL, SQL Server, and/or Snowflake), including ETL workflows and performance tuning
• Strong understanding of data engineering fundamentals, including data modeling, pipelines, validation, lineage, and error handling
• Experience with cloud‑native development on AWS and containerized environments
• Familiarity with distributed systems and event‑driven architectures, such as Kafka
• Experience with CI/CD, DevOps practices, and automated testing
• Exposure to portfolio analytics, risk models, or investment workflows is a plus