Data Engineer

Resilience is a cybersecurity, cyber insurance, and cyber risk management company building integrated solutions for assessing and managing cyber risk. The Data Engineer will own the development, scaling, and optimization of data infrastructure, including pipelines, data models, integrations, cloud systems, governance, and security. The role will also mentor engineers and collaborate with data scientists, analysts, application teams, and non-technical stakeholders.

Responsibilities:

• Design, develop, and maintain robust, scalable data pipelines for ingestion, transformation, and storage, ensuring data quality, reliability, and integrity throughout the pipeline lifecycle
• Partner closely with data scientists, analysts, and application teams to design and implement scalable data models supporting business intelligence and analytics while integrating diverse internal and external sources
• Address system bottlenecks, conduct capacity planning, and implement optimizations to elevate performance and reliability across our cloud-based data systems
• Establish and enforce data security policies, access controls, and compliance standards in alignment with regulatory measures
• Provide technical mentorship to fellow engineers, fostering a culture of continuous learning while communicating technical concepts effectively to non-technical stakeholders

Requirements:

• 3+ years of proven data engineering experience with hands-on expertise in data integration, data modeling, and ETL processes
• Proficiency in programming languages including SQL, Python, and JavaScript/TypeScript
• Solid working knowledge of data warehousing concepts, cloud architectures, and modern data stack tooling (e.g., Dagster, AWS, Snowflake, dbt)
• Familiarity with data governance, security, and compliance best practices
• Bachelor's degree in Computer Science, Data Science, or a related quantitative field (or equivalent practical experience)
• Strong analytical, problem-solving, and cross-functional communication skills, with a track record of managing multiple projects in a dynamic environment
• Master's degree in Computer Science or Data Science
• Advanced certifications in data engineering or cloud platform domains