- Company Name
- Ursus, Inc.
- Job Title
- Fraud Data Engineer
- Job Description
-
**Job Title**
Fraud Data Engineer
**Role Summary**
Design, build, and maintain large‑scale ETL/ELT pipelines for fraud detection and investigation. Leverage Neo4j graph databases, cloud data services (AWS, Azure), and ML feature stores to enable real‑time fraud analytics. Collaborate with data scientists and stakeholders to model complex entity relationships, optimize queries, and enforce data quality, lineage, and governance.
**Expectations**
* 8+ years in data engineering or related field.
* Deep expertise in batch and streaming pipeline design.
* Strong hands‑on experience with Neo4j (data modeling, Cypher, query optimization).
* Proficiency in SQL, Python, and PySpark.
* Ability to integrate ML feature stores, AI workflows, and third‑party threat intelligence APIs.
* Experience with cloud platforms (AWS S3, Azure Blob/VMs).
* Familiarity with orchestration tools (Airflow) and CI/CD (Git, version control).
**Key Responsibilities**
1. Design and implement robust ETL/ELT pipelines (batch & streaming) for structured and unstructured data.
2. Collaborate on Neo4j data modeling, query design, and performance optimization.
3. Build and manage large‑scale ML feature stores and integrate them with AI/ML pipelines.
4. Develop integrations with AWS S3, Azure Blob Storage, VMs, and third‑party threat intelligence APIs.
5. Automate workflows via Apache Airflow or equivalent orchestrators.
6. Apply DataOps practices: version control, CI/CD, monitoring, and documentation.
7. Enforce data quality, lineage, and governance across all data assets.
**Required Skills**
* Data engineering: batch & streaming pipeline design (ETL/ELT).
* Programming: SQL, Python, PySpark.
* Graph database: Neo4j (data modeling, Cypher, query tuning).
* Cloud data services: AWS (S3, etc.), Azure (Blob, VMs).
* Orchestration: Apache Airflow or equivalent.
* DevOps: Git, CI/CD pipelines.
* Data governance: quality, lineage, metadata management.
* Optional: Databricks experience.
**Required Education & Certifications**
* Master’s degree in Statistics, Mathematics, Computer Science, or equivalent.
* Bachelor’s with equivalent professional experience acceptable.