Data Platform Engineer

Fintal Partners; Chicago (IL); On-site; USD 110,000 - 190,000; Full time

Job summary

Fintal Partners, Chicago-based technology-driven financial firm, is seeking a Data Platform Engineer to help design and operate large-scale data infrastructure and analytics. You will work at the intersection of data engineering, production systems, and platform performance.

You will build reliable, observable data workflows, optimize pipelines, and collaborate with engineers and quantitative users in a fast-paced environment to improve the broader data platform.

Qualifications

• 3+ years of experience in Data Engineering, Software Engineering, or Platform Engineering.
• Strong programming experience with Python.
• Hands-on experience with PySpark, Pandas, or similar data-processing technologies.
• Experience building or supporting production ETL/data pipelines.
• Familiarity with Git-based development and CI/CD environments.
• Strong troubleshooting and analytical skills.
• Experience working with large or complex datasets.
• Bachelor's degree in Computer Science, Engineering, or a related technical discipline preferred.

Responsibilities

• Support and improve production data pipelines and ETL workflows.
• Monitor data quality, pipeline reliability, and processing performance.
• Investigate data issues and production failures through root cause.
• Develop monitoring, alerting, automation, and operational tooling.
• Troubleshoot CI/CD and deployment workflows.
• Analyze workload and resource utilization to identify performance bottlenecks.
• Optimize data-processing workflows for reliability and efficiency.
• Work closely with engineering and analytical teams to improve the broader data platform.

Skills

Python

Data engineering

Problem solving

Team collaboration

Education

Bachelor's degree in CS/Engineering

Tools

PySpark

Pandas

Git/CI-CD

Job description

Fintal Partners is working with a leading technology-driven financial firm in Chicago that is looking to add a Data Platform Engineer to a highly technical team responsible for large-scale data infrastructure and analytics.

This position sits at the intersection of data engineering, production systems, and platform performance. You will be responsible for ensuring critical data workflows are reliable, accurate, observable, and efficient while working closely with engineers and quantitative users operating in a fast-paced environment.

Responsibilities

• Support and improve production data pipelines and ETL workflows
• Monitor data quality, pipeline reliability, and processing performance
• Investigate data issues and production failures through root cause
• Develop monitoring, alerting, automation, and operational tooling
• Troubleshoot CI/CD and deployment workflows
• Analyze workload and resource utilization to identify performance bottlenecks
• Optimize data-processing workflows for reliability and efficiency
• Work closely with engineering and analytical teams to improve the broader data platform

Qualifications

• 3+ years of experience in Data Engineering, Software Engineering, or Platform Engineering
• Strong programming experience with Python
• Hands-on experience with PySpark, Pandas, or similar data-processing technologies
• Experience building or supporting production ETL/data pipelines
• Familiarity with Git-based development and CI/CD environments
• Strong troubleshooting and analytical skills
• Experience working with large or complex datasets
• Bachelor's degree in Computer Science, Engineering, or a related technical discipline preferred

Nice to Have

• Experience with distributed or cluster-based computing environments
• Exposure to workload scheduling and resource management
• Experience optimizing high-throughput or performance-sensitive systems
• Background in financial services, trading, or another data-intensive environment