About the role

Design and implement scalable data quality frameworks, automated validation processes, and monitoring solutions across enterprise datasets. Collaborate with data engineering and governance teams to define standards and apply AI-driven techniques for data quality improvement.

What they look for

SQL Python Data quality frameworks Data pipelines ETL/ELT Orchestration tools Data profiling Anomaly detection Root cause analysis Data governance AI/ML Performance tuning Data validation Monitoring techniques

Requirements

Requires a Bachelor's degree and 5 to 7 years of relevant experience in data engineering or quality roles. Candidates must possess advanced SQL skills, programming proficiency in Python, and experience with data pipelines and validation frameworks.

Benefits

401(k) match Health coverage Employee stock purchase plan

Full description

Requisition ID: 263818

Locations: Charlotte

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Job Overview

The Data Quality Engineer III is responsible for designing and implementing advanced data quality frameworks, automated validation processes, and scalable data monitoring solutions across enterprise datasets. This role combines data engineering and data quality expertise to ensure data is reliable, consistent, and fit for analytics and AI use cases. The position also explores and applies AI-driven techniques to improve data quality detection, automation, and continuous monitoring.

Duties & Responsibilities

Design, build, and maintain scalable data quality pipelines, rules, and validation frameworks across enterprise datasets

Develop and optimize data pipelines and orchestration workflows to support data ingestion, transformation, and quality enforcement

Perform advanced data profiling, root cause analysis, and remediation of data quality issues across systems

Implement automated monitoring, alerting, and anomaly detection for data quality across critical data assets

Partner with data engineering, governance, and business teams to define and enforce data quality standards and rules

Develop reusable data quality patterns, documentation, and best practices for enterprise adoption

Explore and implement AI/ML-driven data quality solutions, including anomaly detection, pattern recognition, and intelligent rule generation

Other duties as assigned

Knowledge, Skills, & Abilities

Advanced SQL and data manipulation skills (joins, CTEs, performance tuning)

Strong programming experience (Python preferred)

Experience designing and implementing data quality rules and validation frameworks

Experience with data pipelines, ETL/ELT, and orchestration tools

Knowledge of data profiling, anomaly detection, and monitoring techniques

Familiarity with governance tools (e.g., Alation, Palantir, Informatica, etc.)

Ability to design reusable data quality patterns across datasets

Experience working across structured and semi-structured data

Strong troubleshooting and root cause analysis skills

Minimum Qualifications

Bachelor’s degree (4 years)

5 to up to 7 years

Preferred Qualifications

Bachelor’s degree in Computer Science or Business Administration is preferred

Work Environment

Office

Equal Opportunity Employer - All qualified applicants will be considered for employment without regard to disability, protected veteran status, or any other characteristic protected by applicable law.