Senior Data Engineer

2 days ago

Cincinnati, Ohio, United States Gravity IT Resources Full time
Job Summary

We are seeking a skilled Data Engineer to join our Data Science team at Gravity IT Resources. The ideal candidate will be responsible for designing, building, and maintaining scalable data pipelines and infrastructure to support data analytics, machine learning, and Retrieval-Augmented Generation (RAG) type Large Language Model (LLM) workflows.

Key Responsibilities:

  1. Data Pipeline Development:
  • Design, develop, and maintain robust and scalable ETL (Extract, Transform, Load) processes to ensure data is collected, processed, and stored efficiently and accurately.
  • Integrate data from various sources, including databases, APIs, and third-party data providers, ensuring data consistency and integrity across different systems.
  1. Data Integration:
  • Develop and maintain data pipelines specifically tailored for Retrieval-Augmented Generation (RAG) type Large Language Model (LLM) workflows, ensuring efficient data retrieval and augmentation processes to support LLM training and inference.
  • Collaborate with data scientists to optimize data pipelines for LLM performance and accuracy.
  1. Semantic/Ontology Data Layers:
  • Develop and maintain semantic and ontology data layers to enhance data integration and retrieval, ensuring data is semantically enriched to support advanced analytics and machine learning models.
  1. Collaboration:
  • Work closely with data scientists, analysts, and other stakeholders to understand data requirements and deliver solutions, providing technical support and guidance on data-related issues.
  1. Data Quality and Governance:
  • Implement data quality checks and validation processes to ensure data accuracy and reliability, adhering to data governance policies and best practices.
  1. Performance Optimization:
  • Monitor and optimize the performance of data pipelines and infrastructure, troubleshooting and resolving data-related issues in a timely manner.
  1. Support for Analysis:
  • Support short-term ad-hoc analysis by providing quick and reliable data access, contributing to longer-term goals by developing scalable and maintainable data solutions.
  1. Documentation:
  • Maintain comprehensive documentation of data pipelines, processes, and infrastructure, ensuring knowledge transfer and continuity within the team.

Technical Requirements:

  1. Education and Experience:
  • Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
  • 3+ years of experience in data engineering or a related role.
  1. Technical Skills:
  • Proficiency in Python (mandatory).
  • Experience with other programming languages such as Java or Scala is a plus.
  • Experience with SQL and NoSQL databases (e.g., MySQL, PostgreSQL, MongoDB).
  • Familiarity with big data technologies (e.g., Hadoop, Spark, Kafka).
  • Experience with cloud platforms (e.g., AWS, Azure, Google Cloud) and their data services.
  1. RAG Type LLM Skills:
  • Experience with data pipelines for LLM workflows, including data retrieval and augmentation.
  • Familiarity with natural language processing (NLP) techniques and tools.
  • Understanding of LLM architectures and their data requirements.
  1. Semantic/Ontology Data Layers:
  • Familiarity with semantic and ontology data layers and their application in data integration and retrieval.
  1. Tools and Frameworks:
  • Experience with ETL tools and frameworks (e.g., Apache NiFi, Airflow, Talend).
  • Familiarity with data visualization tools (e.g., Tableau, Power BI) is a plus.
  1. Soft Skills:
  • Strong analytical and problem-solving skills.
  • Excellent communication and collaboration abilities.
  • Ability to work in a fast-paced, dynamic environment.

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