| Generative AI Data Engineer-Pennsylvania(Remote) at Remote, Remote, USA |
| Email: [email protected] |
| Hello Friends, I Hope you are doing well. This is Surya from Humac Inc. , Please check the following job description, and if you are interested, or know someone who might be interested, please share your updated resume to reach you. Role: Generative AI Data Engineer Location: Pennsylvania(Remote) Duration: Long Term Contract Job Description: We are seeking a highly skilled and motivated Generative AI Data Engineer to join our innovative team. The ideal candidate will have a strong background in data engineering and experience with Generative AI technologies. As a Generative AI Data Engineer, you will be responsible for designing, building, and maintaining scalable data pipelines and systems for our cutting-edge AI projects. Responsibilities: Design and develop data pipelines for Generative AI projects by leveraging a combination of technologies, including Vector DB, Graph DB, Airflow, Spark, PySpark, Python, LangChain, AWS Functions, Redshift, and SSIS. This will involve the logical and efficient integration of these tools to create seamless, high-performance data flows that efficiently support the data requirements of our cutting-edge AI initiatives. Collaborate with data scientists, AI researchers, and other stakeholders to understand data requirements and translate them into effective data engineering solutions. Demonstrate familiarity with data integration services such as AWS Glue and Azure Data Factory, showcasing the ability to effectively utilize these platforms for seamless data ingestion, transformation, and orchestration across various sources and destinations. Possess proficiency in constructing data warehouses and data lakes, demonstrating a strong foundation in organizing and consolidating large volumes of structured and unstructured data for efficient storage, retrieval, and analysis. Optimize and maintain data pipelines to ensure high-performance, reliable, and scalable data processing. Develop and implement data validation and quality assurance procedures to ensure the accuracy and consistency of the data used in Generative AI projects. Monitor and troubleshoot data pipeline performance, identify bottlenecks, and implement improvements as necessary. Stay current with emerging trends and technologies in the fields of data engineering, Generative AI, and related areas to ensure the continued success of our projects. Collaborate with team members on documentation, knowledge sharing, and best practices for data engineering within a Generative AI context. Ensure data privacy and security compliance in accordance with industry standards and regulations. Qualifications we seek in you: Minimum qualifications Bachelor's or Master's degree in Computer Science, Engineering, or a related field. Strong experience with data engineering technologies, including Vector DB, Graph DB, Airflow, Spark, PySpark, Python, langchain, AWS Functions, Redshift, and SSIS. Familiarity with Generative AI concepts and technologies, such as GPT-4, Transformers, and other natural language processing techniques. Strong understanding of data warehousing concepts, ETL processes, and data modeling. Excellent problem-solving, analytical, and critical thinking skills. Strong communication and collaboration skills, with the ability to work effectively with cross-functional teams. Preferred Qualifications/ skills Knowledge of cloud computing platforms, such as AWS, Azure, or Google Cloud Platform, is a plus. Experience with big data technologies, such as Hadoop, Hive, or Presto, is a plus. Familiarity with machine learning frameworks, such as TensorFlow or PyTorch, is a plus. A continuous learning mindset and a passion for staying up-to-date with the latest advancements in data engineering and Generative AI. -- Best Regards, Sai Surya Teja US IT Recruiter Humac Inc. P: (623)-748-4074 | Email:[email protected] LinkedIn: linkedin.com/in/sai-surya-1b22a721b Phoenix, AZ 85027 Keywords: artificial intelligence database information technology Arizona |
| [email protected] View all |
| Fri Jan 19 20:55:00 UTC 2024 |