Knowledge Graph Engineer

TekWissen LLC

Job Location:

Frisco, TX - USA

Monthly Salary: Not Disclosed

Posted on: 8 days ago

Vacancies: 1 Vacancy

Job Summary

Overview:

TekWissen is a global workforce management provider headquartered in Ann Arbor Michigan that offers strategic talent solutions to our clients world-wide. Our client provider of digital technology and transformation information technology and services

Position: Knowledge Graph Engineer

Location: Atlanta GA / Frisco TX

Duration: 6 Months

Job Type: Temporary Assignment

Work Type: Hybrid

Job Description :

About the Role:

We are looking for an experienced Knowledge Graph Engineer to design build and scale a production-grade property graph platform that powers customer segmentation device intelligence and household-level insights.
You will own the full lifecycle - from schema design and bulk ingestion to real-time CDC pipelines and graph embedding - working closely with the segment engine team to deliver high-performance traversal queries and ML-ready embeddings at scale.

Key Responsibilities:

Schema Design: Architect the property graph schema defining node types - Customer Device Account Plan Offer - and edge types - HASDEVICE ONPLAN SHARESHOUSEHOLD SIMILARTO - ensuring optimal cardinality and partition key design for scale.
Bulk Load Pipeline: Build and validate the initial bulk load job across the ingestion stack (e.g. Delta Lake S3 staging Neptune bulk loader or equivalent technology).
Real-Time CDC Pipeline: Implement a change data capture pipeline (e.g. Cosmos DB Change Feed Kafka Flink Neptune writer) with an end-to-end lag target of < 60 seconds.
Query Development: Write and optimize Gremlin traversal queries for household segmentation device-sharing patterns and account-linked segmentation use cases.
Index Strategy: Design vertex-centric indexes and leverage Neptune Analytics HNSW for embedding-based similarity lookups.
Graph Embeddings: Build a Node2Vec embedding pipeline (SageMaker or Databricks) and load SIMILARTO edges to support ML-driven similarity features.
Documentation: Document schema definitions traversal patterns and query performance benchmarks for consumption by the segment engine team.

Must-Have Skills & Qualifications:

4 years of graph database engineering experience with production Gremlin / TinkerPop expertise.
AWS Neptune or equivalent cloud graph database - bulk loader operations instance sizing HA configuration and VPC networking.
Apache Kafka and Apache Flink for CDC pipeline design and implementation.
Property graph data modelling - entity resolution edge cardinality and partition key design.
Graph traversal performance profiling at scale (100M nodes).

Nice-to-Have Skills:

Graph embedding algorithms - Node2Vec GraphSAGE or similar.
Neptune Analytics experience for graph analytics workloads.
Neo4j migration or comparative architecture experience (trade-offs vs. Neptune at scale).
Python (gremlinpython) and Java traversal source authoring.
AWS SageMaker or Azure Databricks for embedding model training.

What We Offer:

Opportunity to architect and own a greenfield knowledge graph platform at enterprise scale.
Work with cutting-edge graph and ML technologies across AWS Kafka Flink and SageMaker ecosystems.
Collaborate with data engineering ML and product teams to drive real customer and business impact.
Competitive compensation flexible work arrangements and a culture of continuous learning.

TekWissen Group is an equal opportunity employer supporting workforce diversity.

Overview: TekWissen is a global workforce management provider headquartered in Ann Arbor Michigan that offers strategic talent solutions to our clients world-wide. Our client provider of digital technology and transformation information technology and services Position: Knowledge...