Data Engineer 3 4P/499

4P Consulting
  • Atlanta, Georgia
    30+ days ago

    Job Description

    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

    Numbers & Facts

    LocationAtlanta, Georgia

    Skills

    • Artificial Intelligence (AI)unmatched
    • Automationunmatched
    • Continuous Improvementunmatched
    • Data Analysisunmatched
    • Data Lakeunmatched
    • Data Managementunmatched
    • Data Modelingunmatched
    • Data Qualityunmatched
    • Data Scienceunmatched
    • Documentation Planunmatched
    • EDGE (Enhanced Data for GSM Evolution)unmatched
    • Machine Learningunmatched
    • Model Validationunmatched
    • Oil and Gasunmatched
    • Problem Solving Skillsunmatched
    • Process Improvementunmatched
    • Python Programming/Scripting Languageunmatched
    • Quality Assuranceunmatched
    • Quality Engineeringunmatched
    • Quality Metricsunmatched
    • Requirements Managementunmatched
    • SQL (Structured Query Language)unmatched
    • Software Development Lifecycle (SDLC)unmatched
    • Software Testingunmatched
    • Test Automationunmatched
    • Test Dataunmatched
    • Test Harnessunmatched
    • Test Plan/Scheduleunmatched
    • Test Scriptsunmatched
    • Test Strategyunmatched
    • Test Toolsunmatched
    • Testingunmatched
    • Validation Testingunmatched

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