[Hiring] Senior Data Engineer @Waystar

Role Description

Waystar is seeking a highly skilled Senior Data Engineer to join our Business Data & Architecture team and help advance our enterprise Data Modernization Program on Google Cloud Platform (GCP). This is a senior individual contributor role focused on designing, building, and optimizing scalable data solutions that enable analytics, reporting, governance, and AI initiatives across the enterprise. The ideal candidate is a hands-on engineer with deep technical expertise in cloud data platforms, data modeling, ELT development, and modern engineering practices.

You will work across the full data lifecycle, from data ingestion and transformation to orchestration, quality, observability, and governance, helping deliver trusted and scalable data products that support business decision-making.

Qualifications

• Bachelor’s degree in computer science, Information Systems, Data Engineering, or a related field
• 5+ years of experience in Data Engineering or a related technical discipline
• Strong hands-on experience with Google Cloud Platform (GCP)
• Advanced expertise in BigQuery
• Strong experience with dbt and modern ELT development practices
• Advanced SQL development and query optimization skills
• Strong Python programming experience
• Experience building scalable data pipelines and transformation frameworks
• Experience working with APIs and data integration patterns
• Experience with workflow orchestration tools such as Airflow or Cloud Composer
• Experience with GitHub, source control, and CI/CD development practices
• Strong understanding of dimensional modeling and analytics engineering concepts
• Strong troubleshooting, problem-solving, and analytical skills
• Excellent communication and collaboration skills

Requirements

• Design, build, and maintain scalable ELT pipelines into BigQuery using Fivetran, APIs, Python, and cloud-native services
• Develop and optimize bronze, silver, and gold data layers following Medallion Architecture principles
• Create and maintain reusable dbt models that support enterprise reporting, analytics, and self-service use cases
• Design and implement scalable ingestion patterns for structured and semi-structured data
• Troubleshoot and resolve complex data pipeline, transformation, and performance issues
• Improve pipeline reliability, performance, scalability, and maintainability
• Design and implement scalable data models supporting business intelligence, analytics, and operational reporting
• Partner with business analysts, product owners, and stakeholders to understand and translate requirements into technical solutions
• Develop reusable business-focused datasets and metrics aligned with enterprise standards
• Support semantic modeling and reporting initiatives across business domains
• Contribute to the standardization of enterprise metrics and reporting assets
• Implement automated data validation, testing, and data quality checks
• Develop monitoring, alerting, and observability capabilities across the data platform
• Investigate and resolve data anomalies, processing issues, and performance bottlenecks
• Support operational excellence through logging, incident analysis, and root cause investigations
• Ensure data consistency, accuracy, and reliability across ingestion and transformation processes
• Develop and maintain orchestration workflows using Cloud Composer (Managed Airflow)
• Contribute to CI/CD pipelines using GitHub and modern deployment practices
• Support Infrastructure-as-Code initiatives using Terraform and platform automation tools
• Improve engineering efficiency through automation, reusable components, and standard development patterns
• Participate in platform optimization and modernization initiatives
• Support data classification, lineage, metadata management, and governance initiatives
• Implement secure access controls and data protection practices aligned with enterprise standards
• Partner with Data Governance teams to improve data discoverability and trust
• Ensure compliance with regulatory, privacy, and security requirements
• Contribute to documentation and operational standards for enterprise data assets
• Collaborate with engineers, architects, analysts, and business stakeholders across multiple domains
• Participate in technical design reviews and engineering discussions
• Perform peer code reviews and support engineering quality standards
• Contribute to documentation, knowledge sharing, and reusable engineering practices
• Evaluate new technologies and recommend platform improvements where appropriate

Benefits

• Competitive total rewards (base salary + bonus, if applicable)
• Customizable benefits package (3 medical plans with Health Saving Account company match)
• Generous paid time off for non-exempt team members, starting with 3 weeks + 13 paid holidays, including 2 personal floating holidays
• Flexible time off for exempt team members + 13 paid holidays
• Paid parental leave (including maternity + paternity leave)
• Education assistance opportunities and free LinkedIn Learning access
• Free mental health and family planning programs, including adoption assistance and fertility support
• 401(K) program with company match
• Pet insurance
• Employee resource groups