Senior Data Engineer, Payments

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, Payments based in the United States. Join a data engineering team building the trusted data foundations behind large-scale protection programs and critical business operations. In this senior role, you will design and maintain scalable data pipelines that transform complex internal and external data into reliable, actionable insights. Your work will support financial reconciliation, claims management, operational reporting, product experimentation, and executive decision-making. You will collaborate with cross-functional teams across Engineering, Product, Finance, Operations, Analytics, and Data Science to deliver high-quality data solutions. By strengthening data quality, observability, and modeling practices, you will help the organization scale its protection offerings into new markets. This is an opportunity to combine strong software engineering expertise with data-driven problem-solving in a remote-friendly, collaborative environment.

Design, build, and maintain scalable data pipelines to ingest, reconcile, transform, and publish data for business-critical products and operational workflows. Develop robust, analytics-ready data models and metrics that support financial reconciliation, claims and operations reporting, experimentation, executive dashboards, and self-service analytics. Collaborate with software engineers and external data partners to understand source systems, integrate third-party data feeds, and transform complex information into reliable, consistent datasets. Establish and maintain high standards for data quality, accuracy, consistency, documentation, and ownership across critical data assets. Improve pipeline reliability, maintainability, and observability through automated testing, monitoring, validation, and engineering best practices. Partner with Product, Engineering, Finance, Operations, Analytics, and Data Science teams to translate business needs into effective data solutions that drive measurable outcomes. Contribute to the broader data engineering community by sharing expertise, improving tools and workflows, and influencing technical standards and best practices. Build foundational data systems capable of supporting new markets, evolving product offerings, external partner requirements, and changing regulatory needs. Requirements: At least 6 years of relevant professional experience in data engineering, software engineering, or a closely related technical field. Strong experience designing, developing, and maintaining production-grade ETL or ELT pipelines. Proven expertise in data modeling, including the design of reliable datasets for business analytics, operational workflows, and decision-making. Hands-on experience with large-scale distributed data processing technologies, such as Apache Spark, and distributed storage systems. Advanced SQL skills and proficiency in at least one programming language commonly used in data engineering, such as Python, Scala, or Java. Experience with workflow orchestration and pipeline scheduling frameworks, such as Apache Airflow. Demonstrated ability to work with structured and third-party data sources, reconcile inconsistencies, and transform raw information into trustworthy warehouse models. Strong written and verbal communication skills, with the ability to collaborate effectively with both technical and non-technical stakeholders. Sound technical judgment regarding data quality, testing, documentation, ownership, observability, and long-term maintainability. A proactive, analytical mindset, with the ability to navigate complex data challenges and balance immediate business needs with scalable, sustainable engineering solutions. Nice to have: Experience working with insurance, payments, financial services, risk management, trust, or compliance-related data. Familiarity with external partner data feeds, financial reconciliation processes, and operational reporting systems. Experience supporting experimentation frameworks, executive performance metrics, or business intelligence dashboards. Knowledge of data quality frameworks, automated testing strategies, and observability practices for business-critical datasets. Experience building reusable foundational data assets that serve multiple teams, products, and business use cases. Benefits: Competitive salary: Annual base salary ranging from $196,000 to $227,000 USD , depending on experience, skills, qualifications, and business needs. Performance-based compensation: Potential eligibility for additional bonuses and equity, depending on the role and applicable compensation arrangements. Comprehensive benefits: Access to employee benefits designed to support health, well-being, and financial security. Employee travel credits: Potential eligibility for travel credits as part of the overall compensation package. Remote flexibility: US-remote-eligible position, with occasional office visits or team offsites as agreed upon with the manager. Professional growth: Opportunities to influence data engineering standards, improve foundational systems, and collaborate with experienced professionals across multiple disciplines. Inclusive workplace: A commitment to equal employment opportunities, diversity, accessibility, and reasonable accommodations throughout the recruitment process. Meaningful impact: The opportunity to build reliable data infrastructure that supports customer protection, operational excellence, and informed business decisions at scale.