Data Engineer (Python, Spark, AWS)

We’re looking for a Data Engineer with experience in building scalable, secure, and high-performing web applications that help organizations manage and reduce their cybersecurity risks.

In this role, you will work with cross-functional partners to develop new features, improve existing systems and support our mission of making risk visibility actionable and accessible.

Responsibilities

• Build and enhance web application features that support risk assessment workflows and interactive data visualizations
• Collaborate with team members in Agile ceremonies, sprint planning, and code reviews to ensure consistent delivery.
• Partner with QA to ensure test coverage across unit, integration, and performance layers.
• Contribute to architectural decisions and help improve system reliability and maintainability.
• Participate in production support and help troubleshoot issues as part of an on-call rotation.
• Continuously learn and apply new tools, frameworks, and technologies to improve development workflows and product quality.

Qualifications

• Bachelor's degree in Information Systems, Information Technology, Computer Science or Engineering or equivalent work experience.
• At least 5 years of experience in Python scripting.
• Develop and optimize data pipelines using Python for large-scale data processing.
• Perform big data manipulation and transformation across distributed systems using Spark, Hadoop, AWS.
• Automate data workflows and ensure high performance and reliability.
• Expertise in SQL writing optimized queries and working with relational databases such as Postgres.
• Experience developing applications using Elixir is a plus.
• Deep understanding of core software engineering principles including data structures, design patterns, and clean coding practices.
• Familiarity with Agile development methodologies, including Scrum or Kanban.
• Familiarity with Docker containers, Amazon Web Services (AWS), and Terraform for infrastructure as code.
• Exposure to Ruby, React, HTML, and CSS for full stack development.
• Working knowledge of modern data and infrastructure technologies such as Postgres, MongoDB, Elasticsearch, Kubernetes for container orchestration Kafka for event streaming and messaging.

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