Data Engineering Manager

CYE’s optimized cyber risk quantification platform, Hyver, transforms the way that organizations manage cybersecurity. Hyver visualizes attack routes, quantifies cyber risk, provides evidence-based mitigation plans, improves communication with executives, and improves organizational cybersecurity posture. Hyver’s clear and relevant insights empower companies to make effective cybersecurity decisions.

As a Data Engineering Manager at CYE, you’ll lead a data engineering team and work with product leaders on building and scaling the Hyver SaaS platform.

Our technology stack includes AWS, K8s, Docker, Redis, PostgreSQL, Apache Spark with Databricks and more.

You'll work on:

• Leading a data engineering team
• Designing and implementing real time/near real time/batch data pipelines including data ingestion, data preparation, and data analysis
• Identifying performance bottlenecks and optimizing data processing and storage mechanisms to enhance overall system performance and reduce latency
• Collaborating with cross-functional teams including data analysts, data scientists, product managers, and software engineers to analyze requirements and deliver solutions that meet business needs
• Implementing and enforcing data governance practices and ensuring compliance with relevant regulations and best practices related to data privacy and security
• Providing technical guidance and mentorship to junior data engineers, fostering a culture of learning and growth within the team
  
  

• Bachelor's or Master's degree in computer science, engineering, or a related field
• 2+ years of experience as a data engineering manager
• 5+ years of experience in software development (Python, Java, or Scala)
• 4+ years of experience in data streaming technologies (Apache Spark Structured Streaming, Kafka), including expert knowledge and hands-on experience in building data pipelines using Apache Spark
• Experience with Databricks and Delta Lake or similar Lakehouse technologies
• Proven track record in designing and implementing ETL pipelines, real time/near real time analytics pipelines, data integration, CDC, and data transformation processes