Senior Software Engineer, Data

Cowbell is signaling a new era in cyber insurance by harnessing technology and data to provide small and medium-sized enterprises (SMEs) with advanced warning of cyber risk exposures bundled with cyber insurance coverage adaptable to the threats of today and tomorrow. Championing adaptive insurance, Cowbell follows policyholders' cyber risk exposures as they evolve through continuous risk assessment and continuous underwriting. In its unique AI-based approach to risk selection and pricing, Cowbell's underwriting platform, powered by Cowbell Factors, compresses the insurance process from submission to issue to less than 5 minutes.

Founded in 2019 and based in the San Francisco Bay Area, Cowbell has rapidly grown, now operating across the U.S., Canada, U.K., and India. This growth was recently bolstered by a successful Series C fundraising round of $60 million from Zurich Insurance. This investment not only underscores the confidence in Cowbell's mission but also accelerates our capacity to revolutionize cyber insurance on a global scale. With the backing of over 25 prominent reinsurance partners, Cowbell is poised to redefine how SMEs navigate the evolving landscape of cyber threats.

• Design and implement high-throughput, low-latency FastAPI services to handle real-time and batch workloads for data and AI applications
• Build data pipelines using dbt and Redshift, ensuring models are accurate, scalable, and production-ready
• Work with Amazon Redshift to design, tune, and maintain large-scale analytical data stores.
• Develop and maintain ETL/ELT workflows for ingestion, transformation, and processing of structured and semi-structured data, supporting analytics and business intelligence needs.
• Leverage AWS services (S3, Lambda, Glue, Step Functions, Kinesis, etc.) to build robust, cloud-native data solutions.
• Ensure observability, reliability, and performance tuning for APIs and data workflows handling high-volume operations.
• Data Integration: Work with data from a variety of sources, databases, APIs, and files to create unified datasets optimized for analytics and machine learning.
• Data Quality & Governance: Implement data quality checks with tools like dbt Expectations to maintain data accuracy, integrity, and consistency, and ensure compliance with data governance practices.
• Performance Optimization: Enhance system performance, scalability, and efficiency by optimizing data processing systems.
• Cross Collaboration: Partner with data scientists, analysts, and software engineers to translate business needs into robust data solutions.
• Documentation: Maintain documentation for data architecture, workflows, and systems to support scalability and ease of maintenance.

• Educational Background: A Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or a closely related field.
• Professional Experience: 6+ years in a Software Developer, Data Engineer, or similar role.

Technical Skills:

• Proven expertise in Python (async, concurrency, and multithreading), Pandas, Spark, building FastAPI (or equivalent) services for high-scale, production-grade use cases.
• Strong knowledge of real-time and batch data processing architectures.
• Solid understanding of Amazon Redshift, PostgreSQL performance tuning and query optimization.
• Extensive expertise with AWS ecosystem for data engineering (S3, DMS, Glue, Redshift, EMR, Kinesis, Athena, RDS, Lambda, CloudWatch, ECS, EC2).
• Competency with ETL/ELT principles and distributed systems.
• Strong understanding of data modeling, data architecture, and best practices in data governance.
• Strong problem-solving and communication skills, with the ability to work in fast-paced, cross-functional teams.

Soft Skills:

• Problem-solving abilities with a keen attention to detail.
• Capable of working both independently and within a team setting.
• Strong communication and collaboration skills.
• Flexibility to adapt to new technologies and a commitment to continuous learning.

Preferred Qualifications:

• Exposure to LLM integration and AI-powered APIs.
• Knowledge of Infrastructure-as-Code (Terraform, CloudFormation) and Kubernetes for deploying data/AI services.
• Experience with real-time data streaming technologies (e.g., Kafka, Flink) is a plus.
• Familiarity with containerization (Docker) and orchestration tools (Kubernetes).
• Understanding of data security, compliance, cyber security, and privacy best practices.

Equal Employment Opportunity:

We are committed to equal opportunity in the terms and conditions of employment for all employees and job applicants without regard to race, color, religion, sex, sexual orientation, age, gender identity or gender expression, national origin, disability, or veteran status.

Cowbell is a leading innovator in cyber insurance, dedicated to empowering businesses to always deliver their intended outcomes as the cyber threat landscape evolves. Guided by our core values of TRUE—Transparency, Resiliency, Urgency, and Empowerment—we are on a mission to be the gold standard for businesses to understand, manage, and transfer cyber risk.

At Cowbell, we foster a collaborative and dynamic work environment where every employee is empowered to contribute and grow. We pride ourselves on our commitment to transparency and resilience, ensuring that we not only meet but exceed industry standards.

We are proud to be an equal opportunity employer, promoting a diverse and inclusive workplace where all voices are heard and valued. Our employees enjoy competitive compensation, comprehensive benefits, and continuous opportunities for professional development.

Cowbell is an E-Verify employer. E-Verify is a web-based system that allows an employer to determine an employee's eligibility to work in the US using information reported on an employee's Form I-9. The E-Verify system confirms eligibility with both the Social Security Administration (SSA) and Department of Homeland Security (DHS). For more information, please go to the USCIS E-Verify website.

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Cowbell Cyber does not permit the use of AI tools during any stage of our interview process. By submitting your application, you agree to complete all assessments and interviews without the use of generative AI assistance.