Job Details

Primary Skills

Role: Senior Data Engineer

Work Location: Pittsburgh, PA Preferred, Dallas, TX or Cleveland, OH

Any Visa Restrictions: No   

Role: -

We are seeking an experienced Senior Data Engineer with strong expertise in Python, Neo4j, and graph database technologies. The ideal candidate will have a solid background in data engineering, experience designing and developing graph-based data solutions, and familiarity with AI-related technologies. The candidate will be responsible for building and optimizing data pipelines, managing complex data relationships, and supporting data-driven and AI-enabled initiatives.

Key Responsibilities

• Design, develop, and maintain scalable data pipelines and data engineering solutions using Python.
• Develop and optimize graph database solutions using Neo4j.
• Model complex relationships and interconnected data using graph database technologies.
• Integrate data from multiple sources and ensure data quality, accuracy, and consistency.
• Optimize data processing workflows and database performance.
• Collaborate with cross-functional teams to support AI-driven applications and advanced data analytics initiatives.
• Troubleshoot data pipeline and database issues and implement effective solutions.
• Follow data engineering best practices for data modeling, performance optimization, and solution scalability.

Required Skills & Qualifications

• Strong hands-on experience with Neo4j and graph database technologies.
• Solid experience in Python programming and data engineering.
• Experience designing, developing, and maintaining data pipelines.
• Strong understanding of graph data modeling, relationships, and query optimization.
• Familiarity with AI technologies and their application in data engineering solutions.
• Strong analytical, problem-solving, and communication skills.

Preferred Qualifications

• Experience integrating graph databases with AI and machine learning applications.
• Knowledge of data architecture, data integration, and scalable data processing.
• Experience working with large and complex datasets.