Data Engineer @

1 week ago


Remote, Czech Republic AVENGA Full time
  • 3+ years of experience in data engineering, preferably supporting AI/ML applications.
  • Proficiency in Python, SQL, and vector database query languages.
  • Experience with relational, NoSQL, and vector databases (Snowflake preferred).
  • Hands-on experience with AWS (OpenSearch, S3, Lambda) or Azure (Azure AI Search, Blob Storage, Automation).
  • Experience building scalable ETL/ELT workflows using dbt, Apache Airflow, or similar.
  • Ability to design and integrate RESTful APIs for data exchange.
  • Understanding of data security, encryption, and role-based access controls.
  • Familiarity with Git, CI/CD, containerization (Docker, Kubernetes), and Infrastructure as Code (Terraform, CloudFormation).
  • Experience supporting AI-specific data needs, such as embeddings, Retrieval-Augmented Generation (RAG), and LLM fine-tuning.
  • Strong problem-solving, analytical, and communication skills.
  • English proficiency (C1)
,[Collaborate with AI engineers, data scientists, and developers to integrate LLMs into scalable AI applications., Design and implement scalable, high-performance data pipelines for AI/GenAI applications., Manage and optimize vector databases (e.g., AWS OpenSearch, Azure AI Search) for Generative AI workloads., Build and maintain cloud-based data solutions using AWS (OpenSearch, S3) or Azure (Azure AI Search, Blob Storage)., Implement Snowflake for scalable, cloud-native data storage and processing., Develop ETL/ELT pipelines for real-time and batch data processing., Ensure seamless integration of data pipelines with AI model workflows., Optimize data storage, retrieval, and processing strategies for efficiency and cost-effectiveness., Implement data governance, security best practices, and compliance measures., Set up monitoring, alerting, and logging for data pipelines to ensure reliability.] Requirements: Python, ETL, Data engineering, AWS Lambda, AWS S3, NoSQL, Snowflake, AWS, Azure, AI, dbt, Apache Airflow, REST API, Git, Docker, Kubernetes Additionally: Sport subscription, Training budget, Private healthcare, International projects.

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