Maze
Cybersecurity ⢠AI ⢠Enterprise
Maze is a cybersecurity company that leverages Agentic AI to manage and mitigate vulnerabilities within cloud environments. By automating the investigation and prioritization of vulnerabilities, Maze helps organizations identify critical weaknesses before they can be exploited by attackers. Their innovative approach significantly reduces the backlog of vulnerabilities, focusing on the most pressing security risks and enabling efficient remediation workflows.
11 - 50 employees
Founded 2024
đ Cybersecurity
đ˘ Enterprise
Backend Engineer, Data Engineering
Job not on LinkedIn
November 10
đŽđŞ Ireland â Remote
đľ âŹ100k - âŹ160k / year
â° Full Time
đ Senior
đ´ Lead
đ Backend Engineer
Maze
Cybersecurity ⢠AI ⢠Enterprise
Maze is a cybersecurity company that leverages Agentic AI to manage and mitigate vulnerabilities within cloud environments. By automating the investigation and prioritization of vulnerabilities, Maze helps organizations identify critical weaknesses before they can be exploited by attackers. Their innovative approach significantly reduces the backlog of vulnerabilities, focusing on the most pressing security risks and enabling efficient remediation workflows.
11 - 50 employees
Founded 2024
đ Cybersecurity
đ˘ Enterprise
đ Description
⢠Build Production Data Pipelines: Design, implement, and maintain scalable data pipelines that ingest gigabytes to terabytes of security data daily ⢠Architect Distributed Data Systems: Build and evolve our S3-based data lake infrastructure using Apache Iceberg ⢠Own the Complete Data Lifecycle: Take end-to-end ownership from data ingestion through Kafka streams to transformation via Spark/EMR ⢠Enable Platform Scalability: Build data infrastructure with platform thinking ⢠Optimize for Enterprise Scale: Continuously improve data processing performance and cost efficiency ⢠Drive Technical Excellence: Establish data engineering best practices and mentor team members ⢠Collaborate Cross-Functionally: Work closely with teams to ensure data systems integrate seamlessly
đŻ Requirements
⢠7+ years of software engineering experience with at least 4+ years focused specifically on data engineering ⢠Proven track record building and scaling data ingestion systems that handle gigabytes to terabytes daily ⢠Deep, hands-on production experience with Python, Apache Kafka, and Apache Spark ⢠Strong expertise with AWS data services including S3, EMR, and building data lakes at scale ⢠Proven experience with Apache Iceberg, data lakehouse concepts, and building distributed data systems ⢠Exceptional care and precision in data ingestion and transformation work ⢠Direct experience working at companies that deal with serious data scale ⢠Currently active as a developer, writing production code regularly
đď¸ Benefits
⢠Ambitious Data Challenges: ⢠Expert Team: ⢠Impactful Work: ⢠Build an AI-Native Company: ⢠Technical Growth:
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