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Data Engineer (Atlanta)
Data Engineer (Atlanta)Clear Point Consultants • Atlanta, GA, US
Data Engineer (Atlanta)

Data Engineer (Atlanta)

Clear Point Consultants • Atlanta, GA, US
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No C2C

Were looking for a hands-on Data Engineer to help build, scale, and fine-tune real-time data systems using Kafka, AWS, and a modern data stack. In this role, youll work deeply with streaming data, ETL, distributed systems, and PostgreSQL to power analytics, product innovation, and AI-driven use cases. Youll also get to work with AI / ML frameworks, automation, and MLOps tools to support advanced modeling and a highly responsive data platform.

What Youll Do

  • Design and build real-time streaming pipelines using Kafka, Confluent Schema Registry, and Zookeeper
  • Build and manage cloud-based data workflows using AWS services like Glue, EMR, EC2, and S3
  • Optimize and maintain PostgreSQL and other databases with strong schema design, advanced SQL, and performance tuning
  • Integrate AI and ML frameworks (TensorFlow, PyTorch, Hugging Face) into data pipelines for training and inference
  • Automate data quality checks, feature generation, and anomaly detection using AI-powered monitoring and observability tools
  • Partner with ML engineers to deploy, monitor, and continuously improve machine learning models in both batch and real-time pipelines using tools like MLflow, SageMaker, Airflow, and Kubeflow
  • Experiment with vector databases and retrieval-augmented generation (RAG) pipelines to support GenAI and LLM initiatives
  • Build scalable, cloud-native, event-driven architectures that power AI-driven data products

What You Bring

  • Bachelors degree in Computer Science, Engineering, Math, or a related technical field
  • 3+ years of hands-on data engineering experience with Kafka (Confluent or open-source) and AWS
  • Experience with automated data quality, monitoring, and observability tools
  • Strong SQL skills and solid database fundamentals with PostgreSQL and both traditional and NoSQL databases
  • Proficiency in Python, Scala, or Java for pipeline development and AI integrations
  • Experience with synthetic data generation, vector databases, or GenAI-powered data products
  • Hands-on experience integrating ML models into production data pipelines using frameworks like PyTorch or TensorFlow and MLOps tools such as Airflow, MLflow, SageMaker, or Kubeflow
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