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Maze (mazehq.com)

Backend Engineer (Data Engineering)

Posted Yesterday
Be an Early Applicant
Remote
28 Locations
Senior level
Remote
28 Locations
Senior level
Design and implement scalable data pipelines and architectures for efficient data processing, while collaborating with cross-functional teams and mentoring junior engineers.
The summary above was generated by AI

Summary of the Role:

As a Data Engineer at Maze, 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.

Your Contributions to Our Journey:

  • 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.

  • Optimize for Performance: Continuously monitor and improve data processing performance, security, and scalability.

  • Establish Data Best Practices: Define and enforce 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.

  • Mentor and Lead: As the team grows, mentor junior engineers and lead by example in technical discussions and code reviews related to data systems.

What You Need to Be Successful:

  • Extensive Experience: 7+ years of experience in software engineering with at least 4+ years focused on data engineering

  • Data Processing Mastery: 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 Skills: Strong analytical and problem-solving abilities, with a focus on delivering robust and scalable data solutions.

  • Collaborative Spirit: Excellent communication skills and the ability to work effectively in a cross-functional team.

  • Agility and Adaptability: Comfort working in a fast-paced startup environment with the ability to pivot and adapt as needed.

Why Join Us:

  • Ambitious Data Challenges: We are leveraging advanced data processing techniques to solve some of the most pressing challenges in cybersecurity today. You'll be working with petabytes of security data to uncover insights and enable proactive threat detection.

  • Expert Team: We are a team of hands-on leaders with deep experience in Big Tech and Scale-ups. Our team has been part of the leadership teams behind multiple acquisitions and an IPO.

  • Impactful Work: Cybersecurity is becoming a challenge to most companies and helping them mitigate risk ultimately helps drive better outcomes for all of us.

Top Skills

Airflow
Aws Redshift
Emr
Glue
Java
Kafka
Python
S3
Scala
Spark

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