Data Engineer with Airflow Python Neo4j

Keytag is looking for a strong data engineer to own how data gets captured, moved, and shaped and then turned into a knowledge graph that the rest of the business can actually use.

This is a design and build role. You'll be designing ontology and pipelines from scratch, deciding how varied source data becomes clean, connected, queryable information.

What you'll do

• Build data ingestion pipelines in Python, orchestrated with Airflow working out how to capture data reliably from a range of varied sources
• Extend our AI data platform, the backbone of our Agent Framework
• Model that data as a knowledge graph entities, relationships, the structure that makes it useful (we use Neo4j)
• Transform and serve data as JSON in Redis for fast downstream access
• Explain your thinking clearly to both technical and non-technical people

What we're looking for

• Solid Python real engineering, not just scripting
• Hands-on Airflow experience writing new DAGs and tasks from scratch, not just maintaining existing ones (DAG design, backfills, idempotency, managing dependencies)
• Experience with Neo4j, Cypher, or knowledge graphs generally
• Good instincts for data modelling you can look at source data and reason about how to structure it
• A clear communicator who can talk through a design and defend it
• Someone who can balance speed of delivery against good design, and work iteratively from blank page to useful to finished

Benefits

• Work with talented engineers building AI-powered products that large organizations rely on.
• Friendly and well-organized team with an open communication style.
• Room to keep growing, both your technical and your softer skills
• Remote work, providing flexibility and work-life balance.
• Medical insurance coverage for you and your family.