Senior Graph AI Engineer (Neo4j) - Remote LatAm

Able; United States; Remote; USD 120,000 - 180,000; Full time

Benefits offered by this job

Monthly wellness stipend

Snack boxes delivered to your home

Job summary

Able is seeking a senior graph engineer who loves building data-centric software using Neo4j and Cypher. You will own graph ETL pipelines, ingest high-volume data streams with Kafka, and implement CDC to keep the knowledge graph up to date.

The role emphasizes automated data hygiene and temporal modeling within a scalable graph architecture. You’ll collaborate across teams, implement entity resolution and deduplication, and optimize performance as the graph grows.

Qualifications

• 4+ years of hands-on Neo4j experience with Cypher and schema design.
• Strong background in building data pipelines for graph ingestion.
• Experience with high-volume data ingestion and real-time sync patterns.
• Ability to implement automated data quality checks and entity resolution.
• Proficient in Python for ingestion scripts and maintenance jobs.

Responsibilities

• Architect Graph ETL: design and develop robust ETL pipelines for graph ingestion.
• Data Ingestion at scale: manage high-volume streams using Kafka and implement CDC patterns.
• Automated Graph Hygiene: write scripts for deduplication, orphan node detection, and schema checks.
• Modeling Time: handle complex temporal relationships within the graph.
• Performance Tuning: optimize indexes and storage as the graph grows beyond 25k reports.

Skills

Neo4j

Cypher

Python

ETL Pipelines

Kafka

CDC

Entity Resolution

Data Deduplication

Job description

Able is seeking a senior graph engineer who loves building data-centric software using Neo4j and Cypher. You will own graph ETL pipelines, ingest high-volume data streams with Kafka, and implement CDC to keep the knowledge graph up to date.

The role emphasizes automated data hygiene and temporal modeling within a scalable graph architecture. You’ll collaborate across teams, implement entity resolution and deduplication, and optimize performance as the graph grows.