Backend Engineer (Data Engineering)

Position Overview

• Location Type: Remote
• Employment Type: Full-Time
• Salary: €100K - €160K

Maze is seeking a talented Data Engineer to join our growing team. As a Data Engineer, you’ll play a pivotal role in shaping our data infrastructure and pipeline development. You will have the unique opportunity to design, build, and scale robust data systems from the ground up, influencing everything from architecture decisions to data processing workflows. This is an exciting chance to be at the core of our technical team, driving innovation in how we collect, process, and utilize data to enhance our cybersecurity solutions.

Requirements

• Experience: 7+ years of experience in software engineering with at least 4+ years focused on data engineering.
• Data Processing: Strong experience with data processing frameworks (e.g., Spark, Kafka, Airflow), ETL workflows, and data modeling.
• Database Expertise: Proficiency with both SQL and NoSQL databases, with experience optimizing queries and database performance.
• Cloud Experience: Familiarity with cloud data services (e.g., AWS Redshift, S3, Glue, EMR) and DevOps practices, including CI/CD for data pipelines.
• Programming Skills: Strong coding abilities in Python, Java, or Scala with experience in data manipulation libraries.
• Problem-Solving: Strong analytical and problem-solving abilities, with a focus on delivering robust and scalable data solutions.
• Collaboration: Excellent communication skills and the ability to work effectively in a cross-functional team.
• Agility: Comfort working in a fast-paced startup environment with the ability to pivot and adapt as needed.

Responsibilities

• Data Pipeline Development: Design, implement, and maintain scalable data pipelines that process large volumes of security data efficiently.
• Data Architecture: Architect and develop backend data systems, ensuring they are scalable, maintainable, and secure.
• End-to-End Data Ownership: Take ownership of the entire data lifecycle, from ingestion and storage to processing and visualization.
• Cross-functional Collaboration: Work closely with other engineers, data scientists, and product managers to ensure data systems support product features and analytical needs.
• Performance Optimization: Continuously monitor and improve data processing performance, security, and scalability.
• Best Practices: Establish data quality standards, processing methodologies, and documentation to maintain high-quality data systems.
• Rapid Prototyping: Quickly prototype and iterate on new data solutions, adapting to evolving requirements and emerging technologies.
• Mentorship & Leadership: As the team grows, mentor junior engineers and lead by example in technical discussions and code reviews related to data systems.

Company Information

Maze is a cybersecurity company leveraging advanced data processing techniques to solve some of the most pressing challenges in cybersecurity today. We are building a data-driven approach to threat detection and response.

Application Instructions

• [Instructions on how to apply would be included here if available.]