Data Engineer

Summary

Join Reach Security, a company building self-driving cybersecurity using generative AI, as a Data Engineer. You will design, build, and manage robust data pipelines for analytics within a Datalake or Lakehouse architecture. This role involves developing scalable solutions using Apache Airflow or Dagster to ingest, transform, and manage large volumes of data. You will collaborate with Platform and Product teams, ensuring efficient data strategies and maintaining data integrity. As an early team member, you will establish engineering best practices and identify innovative approaches. Your contributions will be pivotal in building maintainable and dependable software. This position requires a strong background in data engineering and experience with relevant technologies.

Requirements

• 3+ years of experience in data engineering with a specific focus on building and managing data pipelines
• Strong proficiency in Python and experience with Apache Airflow or Dagster
• Expertise in developing solutions within Data Warehouse, Data Lake, and Lakehouse architectures
• Deep understanding of ETL/ELT processes, data transformation techniques, and workflow orchestration
• Experience working with cloud-based data platforms and services (AWS, Azure, GCP, etc.)
• Solid foundation in data modeling, schema design, and optimization techniques
• Excellent problem-solving skills, capable of addressing challenges around data consistency, performance, and scalability
• Strong communication skills with the ability to articulate complex data engineering concepts clearly
• A proactive and collaborative mindset, comfortable working independently and within fast-paced teams
• Must be a US citizen or Green Card holder

Responsibilities

• Design, implement, and maintain scalable and reliable data pipelines using Apache Airflow or Dagster
• Work closely with Platform and Product teams to ensure efficient data ingestion, transformation, and storage strategies
• Develop and optimize data models and schemas that power analytical queries and reporting
• Ensure data integrity, quality, and consistency across Data Warehouse, Data Lake, and Lakehouse environments
• Troubleshoot and optimize performance bottlenecks in complex data processing workflows
• Collaborate in defining engineering best practices, standards, and processes to enhance team productivity and quality
• Proactively identify opportunities to enhance pipeline efficiency, scalability, and reliability

Preferred Qualifications

• Experience with both batch and streaming data pipelines
• Demonstrated expertise in advanced database schema design, query optimization, and database scaling
• Familiarity with Infrastructure as Code (IaC) tools such as Terraform, Pulumi, or AWS CDK
• Proven ability to align data engineering solutions closely with strategic business objectives

Benefits

• Competitive salary and equity
• Comprehensive health, dental, and vision insurance
• Remote work flexibility