Overview
Contract - W2
Skills
ETL
Python
SQL
Nosql
Kafka
JAVA
Best Practices
Technical Specifications
Translate
Data Quality
Problem-Solving
Performance Tuning
Documentation
Machine Learning
GCP
PyTorch
Datasets
Apache Spark
Data Modeling
Excellent Verbal and Written Communication Skills
Data Integration
Natural Language Processing
Computer Vision
Data Pipelines
Maintain Data
Data Warehouses
Unstructured Data
Database Management
Job Details
Job Title: Gen AI Data Engineer
We are seeking a skilled Contract Data Engineer with a strong background in AI to join our team. The ideal candidate will be responsible for designing, building, and maintaining data pipelines and infrastructures that support AI-driven solutions and analytics.
Data Pipeline Development: Design and implement robust data pipelines to collect, process, and store large volumes of structured and unstructured data.
Data Integration: Collaborate with data scientists and AI teams to integrate data from various sources, ensuring data quality and accessibility for machine learning models.
Database Management: Manage and optimize databases and data warehouses to support data retrieval and analytics.
Data Modeling: Create and maintain data models that facilitate the effective analysis of data for AI applications.
Performance Tuning: Monitor and optimize the performance of data systems, ensuring efficient processing and storage.
Documentation: Document data engineering processes, architecture, and standards to ensure clarity and consistency.
Collaboration: Work closely with cross-functional teams to understand data requirements and translate them into technical specifications.
Education: Bachelor's degree in Computer Science, Data Engineering, or a related field; Master's degree preferred.
Experience: Minimum of 3 years of experience in data engineering, with a focus on AI and machine learning projects.
Technical Skills: Proficiency in data engineering tools and technologies (e.g., Apache Spark, Kafka, SQL, NoSQL databases), programming languages (e.g., Python, Java), and cloud platforms (e.g., AWS, Azure, Google Cloud Platform).
Data Modeling: Strong understanding of data modeling techniques and best practices.
ETL Processes: Experience with ETL (Extract, Transform, Load) processes and data integration techniques.
Analytical Skills: Strong analytical and problem-solving skills, with the ability to work with large datasets.
Communication Skills: Excellent verbal and written communication skills, with the ability to convey technical concepts to non-technical stakeholders.
Experience with AI frameworks and tools (e.g., TensorFlow, PyTorch)
Knowledge of machine learning concepts and algorithms.
Knowledge of natural language processing (NLP) and computer vision techniques.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.