Cypress HCM

Data Engineer

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is a Fraud Data Engineer contract position in San Jose, CA, from 12/08/2025 to 12/08/2026, paying $73.71 per hour. Requires 8+ years of data engineering experience, proficiency in SQL, Python, PySpark, and Neo4j, and knowledge of AWS and Azure.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
584
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🗓️ - Date
November 13, 2025
🕒 - Duration
More than 6 months
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🏝️ - Location
Hybrid
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
San Jose, CA
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🧠 - Skills detailed
#Statistics #Cloud #Version Control #ML (Machine Learning) #S3 (Amazon Simple Storage Service) #DataOps #GIT #Data Engineering #Computer Science #Mathematics #Databases #Neo4J #Data Modeling #AWS S3 (Amazon Simple Storage Service) #PySpark #Scala #Data Quality #Storage #Apache Airflow #Graph Databases #Airflow #SQL (Structured Query Language) #AWS (Amazon Web Services) #Azure #Batch #"ETL (Extract #Transform #Load)" #Python #Azure Blob Storage #AI (Artificial Intelligence) #Data Pipeline #Spark (Apache Spark) #Monitoring #Data Science #Databricks
Role description
Job Details • Fraud Data Engineer (Contract) • Location: San Jose, CA 95110 (Hybrid) • Duration: 12/08/2025 to 12/08/2026 • Team: Fraud ADUS About the Role: • Our Consumer Trust team is composed of skilled data engineers, data scientists, and analysts who work collaboratively to detect, prevent, and mitigate fraud. We leverage advanced data platforms, graph technologies, and AI-driven insights to protect our customers and strengthen trust across the ecosystem. • We are seeking an experienced Data Engineering Contractor to help design and scale our next-generation fraud data infrastructure. The ideal candidate should have deep technical expertise in building and optimizing large-scale data pipelines—both batch and real-time—along with experience in graph databases (Neo4j) and modern cloud data platforms. Key Responsibilities: • Design, build, and maintain robust ETL/ELT pipelines (batch and streaming) for structured and unstructured data using SQL and Python/PySpark. • Collaborate with data scientists and business stakeholders to model, query, and visualize complex entity relationships using Neo4j. • Optimize Neo4j data models and Cypher queries for scalability and performance. • Build and manage large-scale ML feature stores and integrate them with AI and agentic workflows. • Develop and maintain integrations across AWS (S3) and Azure (Blob Storage, VMs) , and third-party threat intelligence APIs to enrich fraud detection and investigation workflows. • Automate workflows using Apache Airflow or equivalent orchestration tools. • Apply DataOps best practices, including version control (Git), CI/CD, and monitoring for reliability and maintainability. • Implement and enforce data quality, lineage, and governance standards across all data assets. Required Skills & Qualifications: • Master’s degree in Statistics, Mathematics, Computer Science, or a related field (or bachelor’s degree with equivalent experience) • 8+ years of experience in data engineering or a related field. • Proven success in ETL/ELT design and implementation, including batch and streaming pipelines. • Strong proficiency in SQL, Python, and PySpark. • Hands-on experience with Neo4j (data modeling, Cypher, query optimization). • Experience building ML feature stores and integrating with AI/ML pipelines. • Working knowledge of AWS and Azure data services. • Familiarity with Apache Airflow or similar orchestration tools. • Proficient in Git and CI/CD workflows. • Strong understanding of data quality, lineage, and governance • Nice to Have: Experience with Databricks. Compensation: • $73.71 per hour. #36596625