Data Engineer, Analytics

Data Engineer – Neo4j, Spark & SQLLocation: Charlotte, NC / Dallas, TX (Hybrid Work Model)Employment Type: ContractExperience Required: 5+ Years (7+ Preferred)Role Overview: We are seeking a Data Engineer with strong expertise in Neo4j, SQL, and Spark-based ETL pipelines. The ideal candidate will be responsible for building scalable data pipelines, integrating graph and relational data, and enabling high-quality, secure data platforms.Key ResponsibilitiesData Pipeline DevelopmentDesign, build, and maintain ETL/ELT pipelines using Spark (PySpark/Scala)Process large-scale datasets efficiently across distributed systemsOptimize data ingestion, transformation, and loading workflowsGraph & Relational Data EngineeringWork with Neo4j graph databases for relationship-driven data modelsDevelop and optimize SQL queries for structured data systemsIntegrate graph and relational datasets for unified analyticsData ModelingDesign and implement logical and physical data modelsSupport both: Relational models (SQL-based) and Graph-based models (Neo4j)Ensure scalability and performance of data structuresData Security & GovernanceImplement data security, access controls, and compliance standardsEnsure data quality, integrity, and consistencyFollow best practices for data governance and privacyCollaboration & DeliveryWork with data scientists, analysts, and business teamsTranslate requirements into technical data solutionsParticipate in Agile development cycles and code reviewsMandatory SkillsStrong hands-on experience in: Neo4j (Graph Database), SQL (Advanced Queries & Optimization), Spark (ETL – PySpark/Scala)Experience building data pipelines and ETL workflowsStrong understanding of data modeling conceptsPreferred SkillsExperience with cloud platforms (AWS, Azure, or GCP)Knowledge of data security and governance frameworksFamiliarity with big data ecosystems (Hadoop, Kafka, etc)