Data engineer

Location: Pittsburgh, PA, Cleveland, OH, Dallas, TX, Birmingham, AL or Phoenix, AZWe are seeking a highly skilled Senior Data Engineer with deep expertise in Neo4j and graph technologies to join our growing data team. In this role, you will be responsible for designing, building, and optimizing our enterprise data pipelines, with a specific focus on translating complex, highly connected datasets into scalable graph database architectures.You will bridge the gap between traditional relational/tabular data systems (like Databricks, Snowflake, or SQL) and graph databases, enabling our engineering and analytics teams to perform advanced relationship mapping, network analysis, and real-time graph queries.Key Responsibilities

• Graph Modeling & Architecture: Design, implement, and maintain highly scalable Neo4j graph database schemas (nodes, relationships, labels, and properties) optimized for complex queries and high performance.
• Pipeline Development (ETL/ELT): Build, monitor, and optimize robust data pipelines to ingest large-scale structured and semi-structured data from sources like Databricks, Delta Lakes, Kafka, and cloud storage into Neo4j.
• Query Optimization: Write, debug, and fine-tune complex Cypher queries and APOC procedures to ensure sub-second response times for production applications.
• Graph Data Science (GDS): Collaborate with Data Science teams to implement Neo4j Graph Data Science algorithms (e.g., community detection, centrality, pathfinding) to uncover hidden patterns and insights.
• Database Administration & Scaling: Manage Neo4j cluster deployments, database tuning, memory configuration (pagecache, heap), index/constraint management, and backup/recovery strategies.
• Data Integration: Utilize integration frameworks such as the Neo4j Spark Connector, Neo4j Kafka Connector, or official Python/Java drivers to seamlessly sync graph data with our broader data ecosystem.
• Governance & Security: Implement role-based access controls (RBAC), data security standards, and privacy compliance protocols within the graph ecosystem.

Required Qualifications & Skills

• Experience: 4+ years of data engineering experience, with at least 2+ years of hands-on experience productionizing Neo4j solutions.
• Graph Expertise: Expert-level mastery of Cypher query language and a deep understanding of graph database theory, index design, and query execution planning.
• Core Data Engineering: Strong proficiency in Apache Spark (PySpark/Scala) and experience working within modern cloud data platforms like Databricks or Snowflake.
• Programming Languages: Advanced proficiency in Python, Java, or Scala.
• Big Data Ecosystem: Experience with distributed streaming and processing systems like Apache Kafka and cloud data warehouses.
• Cloud Infrastructure: Hands-on experience with major cloud providers (AWS, Azure, or Google Cloud Platform) and containerization tools like Docker or Kubernetes.