Data Engineer

About the Role Q2, a leading provider of digital banking and lending solutions, seeks a data engineer to build and operate data architecture for our Risk & Fraud team. You will ensure reliable, scalable data that powers fraud analytics, machine learning models, agent interfaces, and customer‑facing tools. Key Responsibilities Design, build, and maintain scalable data pipelines and workflows in a cloud environment Deliver clean, well‑structured datasets to support fraud analytics, machine learning models, and agentic solutions Contribute to improving our data architecture, including ingestion, storage, and access patterns Own data operations by monitoring data workflows, triaging failures, and resolving data issues Enhance observability and performance by implementing monitoring and optimizing pipelines for reliability, scalability, and cost efficiency Partner with product managers, data scientists, and engineers to translate fraud and risk requirements into data solutions Write maintainable code; participate in code reviews; help improve testing, deployment, and documentation standards Production support: review pipeline executions, investigate and resolve failures Develop and orchestrate pipelines, defining data flow, transformations, and dataset relationships Monitor and optimize pipelines for performance and efficiency Collaborate with teams and stakeholders to understand data requirements and ensure platform solutions meet business needs Requirements Typically requires a Bachelor’s degree in a relevant field and a minimum of 2 years of related experience; or an advanced degree without experience; or equivalent work experience. Experience building and maintaining data pipelines and workflows in production environments Proficiency in SQL and working with relational and/or analytical data stores Experience with Python Familiarity with data modeling, transformation, and orchestration concepts Experience with data warehouses and distributed data processing systems Experience with version control (e.g., Git) and CI/CD practices Ability to troubleshoot data issues, debug pipelines, and work through ambiguous problems Nice to Have Experience with tools such as Apache Airflow, dbt, Kafka, Airbyte, or FiveTran Experience with Snowflake or similar cloud data warehouses Experience with SQL Server, PostgreSQL, or NoSQL systems like DynamoDB Familiarity with infrastructure as code tools such as Terraform Experience with Docker and/or Kubernetes Exposure to platforms like Databricks, AWS Glue, AWS SageMaker, Snowpark Benefits Hybrid Work Opportunities Flexible Time Off Career Development & Mentoring Programs Health & Wellness Benefits, including competitive health insurance offerings and generous paid parental leave for eligible new parents Community Volunteering & Company Philanthropy Programs Employee Peer Recognition Programs – "You Earned it" Legal and Compliance Applicants must be authorized to work for any employer in the U.S. We are unable to sponsor or take over sponsorship of an employment visa at this time. We are an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, genetic information, or veteran status. Applicants in California or Washington State may not be exempt from federal and state overtime requirements. #J-18808-Ljbffr Q2