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Data Engineering Lead -Remote

We are a diverse and globally distributed team working on a cutting-edge cybersecurity SaaS product, designed to offer actionable insights into cyber threats and risk management strategies. Our product leverages complex data models and machine learning to provide real-time threat intelligence and risk assessments to our clients.

Key Points

Remote

Must be able to sync with UK/ Western Europe time zones.

Long-Term Contract

 Starting with a commitment of 3 days a week.

Language

English

Key Requirements

We are seeking a Data Engineering Lead to empower our team, improve one of our most complex algorithms, and implement the integration of our data pipeline, specifically focusing on graph database management and data architecture.

  • Proven experience in team leadership and software engineering, with a strong portfolio demonstrating previous work in data engineering.

  • Expertise in Python and familiarity with graph database engineering, including designing and managing directed graph databases.

  • Capability to work productively in a remote setting, with excellent skills in asynchronous communication and time management.

  • A deep understanding of graph concepts and experience with graph databases, preferably with knowledge of Neo4j.

  • Familiarity with ML / LLM concepts (coding skills not mandatory, but a strong understanding is required).

  • Experience in working with cybersecurity standards (STIX, NIST, etc.) is highly desirable.

What You Will Be Solving?

Developing and managing a data pipeline from a Neo4j Graph Database, structured as a directed graph encompassing incidents, victims, attacks, actors/malware, TTPs, and courses of action/controls.
Ensuring effective ingestion into RDB/Document Storage for Web Service integration.
Performing calculations based on many-to-many one-directional relationships within the graph.

Key Responsibilities

  • Lead the data engineering team, guiding both strategy and execution in data modeling, pipeline development, and database architecture.

  • Design and implement a cohesive dataset by integrating various components, with a strong focus on graph databases.

  • Iterate quickly on product development, adapting to new requirements and changes in focus with agility.

  • Work remotely, efficiently managing tasks and communication primarily asynchronously, with regular scheduled meetings.

  • Drive projects both independently and in collaboration with the team, aligning closely with UK / Western Europe time zones.

  • Enhance our product's data architecture, ensuring scalability and effectiveness of the graph database engineering.

  • Contribute to machine learning and large language model (LLM) components of the project, applying an understanding of these technologies to inform data strategy and product features.

Nice to Haves

  • Experience with DevOps and pipeline management.

  • In-depth knowledge of Neo4j.

  • Advanced expertise in machine learning and large language models.

  • Proficiency in Node (JavaScript).

Apply Today

Submit your CV and Cover letter to our email ops@elemendar.ai

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