Data Engineer II
Five9
| Company | Five9 |
| Category | Engineering |
| Location | India |
| Remote | On-site (inferred) |
| Employment | Not stated |
| Level | Not stated |
| Salary | Not stated by the employer |
| Posted | 15 Jul 2026 |
| Last verified | 30 Jul 2026 |
| Source | Employer career page (greenhouse) |
Description
Join us in bringing joy to customer experience. Five9 is a leading provider of cloud contact center software, bringing the power of cloud innovation to customers worldwide.
Living our values everyday results in our team-first culture and enables us to innovate, grow, and thrive while enjoying the journey together. We celebrate diversity and foster an inclusive environment, empowering our employees to be their authentic selves. Senior Data Engineer Five9 is a leading provider of cloud software for the enterprise contact center market. Our platform delivers a secure, reliable, compliant, and scalable solution that empowers organizations to create exceptional customer experiences, boost agent productivity, and achieve meaningful business results. At Five9, we live our values every day—fostering a team-first culture that promotes innovation, growth, and collaboration. We celebrate diversity and maintain an inclusive environment that empowers our employees to bring their authentic selves to work. Position Overview: We are seeking a skilled and proactive Senior Data Engineer to join our growing Finance Data Engineering team. This role will focus on designing and implementing data extraction and integration solutions from enterprise systems such as Salesforce, Jira, NetSuite, and Logisense, leveraging REST/SOAP APIs and Python within the Google Cloud Platform (GCP). The Senior Data Engineer will build and manage scalable data pipelines using tools such as Dataform, Airflow, Cloud Run Functions, and Workflows, with infrastructure managed as code via Terraform, ensuring seamless access to data for analytics, business intelligence, and data science initiatives. A key focus of this role is building AI agents and AI-powered tools to automate manual workflows and improve team productivity. This role will collaborate closely with business stakeholders and cross-functional teams to support a wide range of strategic projects. The ideal candidate brings strong technical expertise in data engineering, a solid understanding of data warehousing principles, and the ability to translate technical processes into clear documentation. This position requires working in the PST time zone to support production jobs and month-end close cycles. Key Responsibilities: • Collaborate with stakeholders across the Finance team to understand business requirements and translate them into well-defined, actionable data sets for analysis and reporting. • Design, develop, and maintain scalable data extraction and ELT pipelines in Google Cloud Platform (GCP) to process structured and unstructured data from diverse sources including databases, REST/SOAP APIs, and cloud storage systems. • Leverage a suite of GCP services such as Big Query, Dataform, Cloud Run Functions, Workflows, Airflow, Pub/Sub, and Cloud Storage to build efficient, secure, and high-performing data workflows. • Manage infrastructure as code using Terraform and maintain code and CI/CD pipelines in GitLab following branching, review, and deployment best practices. • Build, test, and maintain AI agents and internal AI tooling to automate repetitive data engineering and finance workflows and improve productivity across the team. • Continuously monitor and optimize data pipelines for performance, scalability, reliability, and cost-efficiency. • Manage and monitor scheduled production jobs (Daily, Weekly, Bi-Weekly, and Monthly), ensuring timely and accurate data processing across all cycles during PST business hours. • Provide production support during critical month-end data load windows (Day 1 to Day 5), ensuring data availability and resolving issues swiftly to meet business reporting deadlines. • Maintain clear and thorough technical documentation and runbooks for data pipelines, workflows, integrations, and system architecture to support ongoing development and cross-functional collaboration. • Support Looker dashboards and ML models that serve financ