What are the responsibilities and job description for the Data Engineer 3 4P/499 position at 4P Consulting Inc.?
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
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Design, develop, and execute data quality tests for data moving through relational systems and data lakes
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Monitor, validate, and enforce data integrity, accuracy, and consistency
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Identify, document, and resolve data issues across ingestion, transformation, and analytics layers
AI & Machine Learning QA
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Implement QA testing strategies for AI and machine learning models
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Validate model inputs, outputs, and performance against defined requirements
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Work closely with data scientists and engineers to ensure reliable and trustworthy AI solutions
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Support testing of model retraining, versioning, and deployment pipelines
Automation & Engineering
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Develop and maintain automated testing frameworks for data pipelines and AI models
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Write and maintain test scripts using Python and SQL
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Apply strong data modeling principles to support scalable and testable architectures
Collaboration & Continuous Improvement
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Partner with data engineers, ML engineers, and product teams to improve data and model quality
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Support continuous improvement of QA processes and software development lifecycle
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Document test plans, results, and quality metrics clearly for technical and business stakeholders
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5–10 years of experience in data engineering, data QA, or software testing
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Hands-on experience testing data pipelines and analytics platforms
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Experience supporting AI/ML model validation and testing
Technical Skills
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Strong proficiency in Python and SQL
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Deep understanding of data modeling and data lake architectures
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Experience with automation testing tools and frameworks
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Strong knowledge of machine learning concepts, workflows, and frameworks
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Experience validating AI analytical models and data-driven systems