Bachelor's degree in Computer Science, Software Engineering, or a related field
3 years of experience as a Data Engineer, focusing on machine learning and predictive analytics
Proficient in Spark or Python for building real-time and batch data pipelines
Experience integrating machine learning models into production data pipelines
Strong understanding of distributed data processing and ML workflow integration
Responsibilities
Design and implement predictive analytics pipelines using Spark or Python
Develop data workflows for preprocessing and feeding data into machine learning models
Integrate ML models into pipelines for automated inference and continuous learning
Optimize data pipelines for performance, scalability, and reliability
Collaborate with data scientists to ensure integration of ML models
Monitor and troubleshoot pipelines to maintain data quality and model accuracy
Benefits
Competitive salary and comprehensive benefits package including healthcare, PTO, 401k
Opportunities for professional growth and upskilling in AI and cloud technologies
Full Job Description
Overview:
ML-Driven Data Engineer (Predictive Analytics Pipelines)
Location: Alpharetta, GA (willing to travel to client locations)
Employment Type: Full-Time (W2)
Role Overview
We are seeking a skilled ML-Driven Data Engineer to build predictive analytics pipelines using Spark or Python. This role focuses on developing real-time and batch pipelines to support machine learning models for actionable insights.
Key Responsibilities
Design and implement predictive analytics pipelines using Spark or Python for real-time and batch processing.
Develop data workflows to preprocess and feed data into machine learning models for analytics.
Integrate ML models into pipelines for automated inference and continuous learning in production.
Optimize data pipelines for performance, scalability, and reliability in distributed environments.
Collaborate with data scientists to ensure seamless integration of ML models into data workflows.
Monitor and troubleshoot pipelines to maintain data quality and model accuracy over time.
Required Qualifications
Bachelor's degree in Computer Science, Software Engineering, or a related field (or equivalent experience).
3 years of experience as a Data Engineer with a focus on machine learning and predictive analytics.
Proficiency in building real-time and batch pipelines using Spark or Python for ML-driven applications.
Experience integrating machine learning models into data pipelines for production use.
Strong understanding of distributed data processing and ML workflow integration.
Preferred Qualifications
Familiarity with cloud-based ML platforms like AWS SageMaker or Azure ML for pipeline integration.
Exposure to advanced Spark features like MLlib for building predictive analytics models.
Knowledge of orchestration tools like Airflow for managing complex ML pipelines.
Compensation & Benefits
Competitive salary and comprehensive benefits package (healthcare, PTO, 401k).
Opportunities for professional growth and upskilling in AI and cloud technologies.
