Data Quality Engineer

Nexiva • St Louis, MO

1d • Onsite

About The Position

As a Senior Software Engineer focused on Data Quality, you will lead the design, development, and deployment of scalable data quality frameworks and pipelines. You will work closely with data engineers, analysts, and business stakeholders to build solutions that validate, monitor, and improve data quality across large-scale distributed systems. The role is onsite in St. Louis, Missouri, in the investment banking client domain.

Requirements

• Bachelor's or master's degree in Computer Science, Engineering, or a related field, with Data Engineering experience.
• At least 5 years of professional software development experience, including at least 2 years in a lead or senior engineering role.
• Strong proficiency in Python and experience building data processing applications.
• Hands-on expertise with Apache Spark and Hadoop for big data processing.
• Experience with workflow orchestration tools such as Apache Airflow.
• Experience designing and managing data ingestion and integration pipelines with Apache NiFi.
• Understanding of data quality automation, CI/CD, Jenkins, Oracle, Power BI, and Splunk.
• Deep understanding of data quality concepts, data validation techniques, and distributed data systems.
• Strong problem-solving skills and ability to lead technical discussions.
• Excellent communication and collaboration skills.
• Local candidates required; genuine driver's license required.
• GC or US citizen candidates only.

Nice To Haves

• Experience with cloud platforms such as AWS, GCP, or Azure.

Responsibilities

• Lead the design and implementation of data quality frameworks and automated validation pipelines using Python, Apache Spark, and Hadoop ecosystem tools.
• Develop, deploy, and maintain scalable ETL/ELT workflows using Apache Airflow and Apache NiFi for data ingestion, transformation, and quality checks.
• Collaborate with cross-functional teams to understand data quality requirements and translate them into technical solutions.
• Define and enforce data quality standards, rules, and monitoring processes.
• Perform root cause analysis on data quality issues and implement fixes and enhancements.
• Mentor and guide junior engineers, conduct code reviews, and foster best practices.
• Evaluate and integrate tools and technologies to enhance data quality capabilities.
• Ensure code quality, performance, and reliability in data processing pipelines.
• Create documentation and reports on data quality metrics and system architecture.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior