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4P Consulting Inc.

Data Engineer 3 4P/499

4P Consulting Inc., Atlanta, Georgia, United States, 30383

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Data Engineer 3 – Quality Assurance (AI & Data Platforms)

Location - Atlanta, Ga

Client - Southern Company Gas

Contract - 10 Months

Position Overview We are seeking an experienced

Data Engineer – Quality Assurance

to support data quality, testing, and validation across our AI-driven analytics platform. This role is focused on

testing data and AI analytical models

as data flows through a

data lake architecture , ensuring accuracy, reliability, and performance.

As a

Quality Assurance Data Engineer

within the

EDGE group , you will play a critical role in enforcing data quality standards, validating machine learning models, and supporting continuous improvement of our data and AI systems through both

manual and automated testing .

Key Responsibilities Data Quality & Testing

Design, develop, and execute

data quality tests

for data moving through relational systems and data lakes

Monitor, validate, and enforce

data integrity, accuracy, and consistency

Identify, document, and resolve data issues across ingestion, transformation, and analytics layers

AI & Machine Learning QA

Implement

QA testing strategies for AI and machine learning models

Validate model inputs, outputs, and performance against defined requirements

Work closely with data scientists and engineers to ensure reliable and trustworthy AI solutions

Support testing of model retraining, versioning, and deployment pipelines

Automation & Engineering

Develop and maintain

automated testing frameworks

for data pipelines and AI models

Write and maintain test scripts using

Python and SQL

Apply strong

data modeling

principles to support scalable and testable architectures

Collaboration & Continuous Improvement

Partner with data engineers, ML engineers, and product teams to improve data and model quality

Support continuous improvement of QA processes and software development lifecycle

Document test plans, results, and quality metrics clearly for technical and business stakeholders

Experience

5–10 years of experience in

data engineering, data QA, or software testing

Hands-on experience testing

data pipelines and analytics platforms

Experience supporting

AI/ML model validation and testing

Technical Skills

Strong proficiency in

Python and SQL

Deep understanding of

data modeling

and data lake architectures

Experience with

automation testing tools and frameworks

Strong knowledge of

machine learning concepts, workflows, and frameworks

Experience validating AI analytical models and data-driven systems

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