Data Engineer

Resilience

3d•$100,000 - $140,000•Remote

About The Position

At Resilience, we’re creating a new category that integrates cybersecurity, cyber insurance, and cyber risk management. Founded in 2016 by experts from across the highest tiers of the US military and intelligence communities – and built by prominent leaders and innovators from the insurance, technology, and cybersecurity industries – Resilience is rewriting the rules of how cyber risk is assessed, measured, and managed. Our integrated cyber risk solutions connect risk quantification software, cybersecurity experts, and A+ rated cyber insurance, all purpose-built for middle and large organizations. We are a cybersecurity company, a Cyber and Tech E&O-focused MGA, a fintech startup, and a data science powerhouse, all purposefully built into one. Resilience is proud to be backed by leading technology investment firms, including General Catalyst, Lightspeed Venture Partners, Intact Ventures, Founders Fund, CRV, and Shield Capital. Step into a critical technical role driving the core data architecture that powers our category-defining platform. As a Data Engineer at Resilience, you won't just maintain existing pipelines; you will take full ownership of building, scaling, and optimizing the data infrastructure that connects cybersecurity visibility with cyber insurance analytics. Sitting at the heart of our engineering team, you will ensure efficient and reliable data integration, storage, and processing across cross-functional teams, transforming complex datasets into seamless, high-performance systems.

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.

Nice To Haves

Master's degree in Computer Science or Data Science.
Advanced certifications in data engineering or cloud platform domains.

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.