Data Engineer - Neo4j - Hybrid
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Job description
We are looking for experienced Data Engineers to work on next-generation AI-enabled data platforms and Knowledge Graph initiatives. This role focuses on building scalable data pipelines, modeling enterprise data, and integrating datasets into graph-based systems like Neo4j to support advanced analytics and GenAI use cases., Build and maintain scalable ETL/ELT pipelines for structured and unstructured data Develop data ingestion workflows into relational and graph databases (Neo4j or similar) Design and implement logical and physical data models for analytics and operational systems Develop data transformation pipelines for enterprise datasets (risk, controls, policy, etc.) Ensure data security, governance, and access controls across pipelines Optimize SQL queries and overall data performance Support graph data modeling, including relationship mapping and entity linkage Build monitoring, logging, and observability mechanisms for data pipelines Collaborate with AI/analytics teams to support GenAI and advanced analytics workflows Maintain documentation, data lineage, and operational runbooks, This early-career fullstack role is tailored for recent graduates eager to accelerate their growth by building impactful products. You will contribute to and gradually take ownersh…
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Requirements
If you have strong hands-on experience in SQL, ETL, and data modeling, and are interested in working on modern data architectures involving graph databases and AI workflows, this role will be a strong fit., 6+ years of experience in Data Engineering Strong expertise in SQL Hands-on experience building ETL/ELT pipelines Solid experience in data modeling (dimensional, star schema, normalized models) Understanding of data security, governance, and access control Experience with Neo4j or any graph database Experience with Python, Spark, or modern data tools Strong troubleshooting and performance tuning skills Preferred Skills Experience working with AI/ML data pipelines or GenAI workflows Domain experience in Banking, Risk, or Compliance Experience with orchestration tools like Airflow, Control-M, or Autosys Exposure to cloud platforms (AWS, Azure, or GCP)