Senior Data Engineer

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Data Engineer based in United States. As a Senior Data Engineer, you will build and operate the data infrastructure that supports critical business and customer-facing decisions. This is a hands-on engineering role focused on production-grade Python and SQL, resilient pipelines, data modeling, and cloud data warehouse architecture. You will work with Snowflake, Airflow, and Data Vault 2.0 to ensure data remains accurate, trusted, observable, and readily available to stakeholders. Your work will directly support areas such as pricing, underwriting, financial reporting, and customer operations. Beyond technical delivery, you will develop deep expertise in insurance data and business processes while partnering with engineering, product, executive, and business teams. You will also help shape engineering standards around testing, governance, security, reliability, cost efficiency, and the effective use of AI-powered development tools. This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Data Engineer based in United States. As a Senior Data Engineer, you will build and operate the data infrastructure that supports critical business and customer-facing decisions. This is a hands-on engineering role focused on production-grade Python and SQL, resilient pipelines, data modeling, and cloud data warehouse architecture. You will work with Snowflake, Airflow, and Data Vault 2.0 to ensure data remains accurate, trusted, observable, and readily available to stakeholders. Your work will directly support areas such as pricing, underwriting, financial reporting, and customer operations. Beyond technical delivery, you will develop deep expertise in insurance data and business processes while partnering with engineering, product, executive, and business teams. You will also help shape engineering standards around testing, governance, security, reliability, cost efficiency, and the effective use of AI-powered development tools. Accountabilities Develop complex, efficient data pipelines that transform raw sources into reliable, well-tested components of enterprise data models. Design, build, and maintain resilient pipelines that provide accurate, trusted data with the freshness required by business and technical stakeholders. Make data modeling decisions within a Data Vault 2.0 architecture, balancing raw data fidelity with the consumption requirements of downstream marts and analytics. Administer and optimize Snowflake environments, including warehouse sizing, query performance, access controls, Role-Based Access Control (RBAC), user and role management, and cost optimization. Build and maintain resilient Apache Airflow Directed Acyclic Graphs (DAGs) and Continuous Integration/Continuous Delivery (CI/CD) pipelines to make deployments predictable, repeatable, and safely reversible. Implement automated unit, integration, and data-quality testing to identify issues during development and Continuous Integration (CI) before they reach production. Own production observability through internal tooling, including alert tuning, incident response, and connecting production issues back to pre-load validation and CI improvements. Use AI-powered development tools such as Claude Code, Cursor, and Snowflake Cortex to accelerate development, automate documentation, and improve software quality. Partner with Executive, Product, Engineering, and business stakeholders to understand the underlying business need and translate it into effective technical solutions. Lead technical projects end-to-end, including scoping, requirements documentation, technical decision-making, stakeholder communication, and delivery. Drive cross-functional initiatives that require influence, alignment, and collaboration across multiple teams. Establish and promote best practices for data governance, privacy, security, change management, and validation, particularly for Sarbanes-Oxley (SOX)-relevant reporting. Take ownership of operational data infrastructure responsibilities with a focus on reliability, observability, performance, and cost efficiency. Build and deepen domain expertise in insurance, including premium, loss, and policy lifecycle concepts, to improve the quality and business relevance of data solutions. Requirements 5+ years of experience as a Software Engineer or Data Engineer with a strong focus on data systems. Advanced proficiency in complex SQL and experience working with large structured and semi-structured datasets. Strong proficiency in Python for developing production-grade data pipelines. Hands-on experience administering Snowflake, including warehouse management, RBAC and role design, access controls, and cost governance. Demonstrated experience designing and implementing modern data warehouses using platforms such as Snowflake, Amazon Redshift, or Google BigQuery. Experience with Data Vault 2.0 is strongly preferred; deep dimensional modeling experience is also relevant, provided you are willing to develop expertise in Data Vault. Proven experience using testing frameworks to validate data pipelines and production code. Hands-on experience with data observability tools and practices. Proficiency using AI-powered coding assistants such as Claude Code, Cursor, or Snowflake Cortex as an integral part of your development workflow. Track record of independently leading technical projects from initial scoping through documentation, delivery, and stakeholder communication without relying on a Product Manager. Strong understanding of data reliability, governance, privacy, security, and operational best practices. Comfortable working in regulated environments, including those involving SOX-relevant financial reporting. Strong communication and collaboration skills, with the ability to explain technical concepts and trade-offs to both technical and business stakeholders. Willingness and ability to develop deep expertise in insurance and understand concepts such as premium, loss, and policy lifecycle alongside technical data systems. Benefits Base compensation range of $140,000–$175,000 USD . Competitive cash compensation. Potential eligibility for discretionary annual bonuses based on company performance. Comprehensive health plans. Generous paid time off (PTO). 401(k) retirement plan with employer matching. Generous parental and caregiver leave. Remote work opportunity for employees living and working in the United States, excluding U.S. territories. Requirement for remote employees to have reliable, high-speed internet access. A collaborative work environment centered on transparency, strong operating principles, and teamwork. An opportunity to work on data infrastructure supporting critical pricing, underwriting, financial reporting, and insurance operations. How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best! Why Apply Through Jobgether? Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time. #LI-CL1