Data Engineer
Listed on 2026-02-28
-
IT/Tech
Data Engineer, Data Analyst, Data Science Manager, Data Scientist
To Apply for this Job
Role: Data Engineers
Location: Hybrid
- Cincinnati, OH
Duration: Six Months Contract
Eligibility: U.S. Citizen Only
Job Summary: We are seeking three skilled Data Engineer to join our Data Science team. 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. This role requires a strong technical background, excellent problem-solving skills, and the ability to work collaboratively with data scientists, analysts, and other stakeholders.
Key Responsibilities:
- Design, develop, and maintain robust and scalable ETL (Extract, Transform, Load) processes.
- Ensure data is collected, processed, and stored efficiently and accurately.
- Integrate data from various sources, including databases, APIs, and third-party data providers.
- Ensure data consistency and integrity across different systems.
- Develop and maintain data pipelines specifically tailored for Retrieval-Augmented Generation (RAG) type Large Language Model (LLM) workflows.
- Ensure 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.
- Develop and maintain semantic and ontology data layers to enhance data integration and retrieval.
- Ensure data is semantically enriched to support advanced analytics and machine learning models.
- Work closely with data scientists, analysts, and other stakeholders to understand data requirements and deliver solutions.
- Provide technical support and guidance on data-related issues.
- Implement data quality checks and validation processes to ensure data accuracy and reliability.
- Adhere to data governance policies and best practices.
- Monitor and optimize the performance of data pipelines and infrastructure.
- Troubleshoot and resolve data-related issues in a timely manner.
- Support short-term ad-hoc analysis by providing quick and reliable data access.
- Contribute to longer-term goals by developing scalable and maintainable data solutions.
- Maintain comprehensive documentation of data pipelines, processes, and infrastructure.
- Ensure knowledge transfer and continuity within the team.
Technical Requirements:
- 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.
Skills:
- Proficiency in Python (mandatory).
- Experience with other programming languages such as Java or Scala is a plus.
- Experience with SQL and No
SQL databases (e.g., MySQL, Postgre
SQL, Mongo
DB). - Familiarity with big data technologies (e.g., Hadoop, Spark, Kafka).
- Experience with cloud platforms (e.g., AWS, Azure, Google Cloud) and their data services.
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.
- Familiarity with semantic and ontology data layers and their application in data integration and retrieval.
- 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.
- Strong analytical and problem-solving skills.
- Excellent communication and collaboration abilities.
- Ability to work in a fast-paced, dynamic environment.
Preferred Qualifications:
- Experience with machine learning and data science workflows.
- Knowledge of data governance and compliance standards.
- Certification in cloud platforms or data engineering.
Equal Employment Opportunity Statement
Gravity IT Resources is an Equal Opportunity Employer. We are committed to creating an inclusive environment for all employees and applicants. We do not discriminate on the basis of race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, age, disability, genetic information, veteran status, or any other legally protected characteristic. All employment decisions are based on qualifications, merit, and business needs.
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