Senior Data Engineer

Gong harnesses the power of AI to transform how revenue teams win. The Gong Revenue AI Operating System unifies data, insights, and workflows into a single, trusted system that observes, guides, and acts alongside the world’s most successful revenue teams. Powered by the Gong Revenue Graph, AI-powered intelligence, specialized agents, and trusted applications, Gong helps more than 5,000 companies around the world deeply understand their teams and customers, automate critical sales workflows, and close more deals with less effort. For more information, visit www.gong.io. At Gong, you will join a company built on innovative products, ambitious goals, and passionate people. We are shaping the future of revenue intelligence and we want people who are excited to build what comes next. You will work with a team that dreams big, moves fast, and cares deeply about the craft and about each other. Here, transparency and trust are core to how we operate, and every person has the opportunity to make a visible impact. If you want to grow, stretch, and do work that truly matters, Gong is the place to do the best work of your career. As an Senior Data Engineer, you will help the DataOps team build the data transport, collection, and storage, and expose services that make data accessible to all of Gong’s business data platforms. We are seeking a Data Engineer to develop a scalable data platform. You'll have ownership of our core business data pipeline that powers Gong’s top-line metrics. You will also use data expertise to help evolve data models in several components of the data stack. You will help architect, build, and launch scalable data pipelines to support Gong’s growing data processing and analytics needs. Your efforts will allow access to business and user behavior insights, using Gong’s data to fuel several teams across the organization. Role Summary: We are looking for a Senior Data Engineer to join our IT Infrastructure team. This role will focus on building, optimizing, and maintaining our data infrastructure to support business analytics, data integration, and automation efforts. You will work with a modern stack—including GCP, AWS, Snowflake, Jenkins, dbt, Retool, Tableau, and Workato—to ensure data flows efficiently and securely across the organization. You are a strong self-starter with the ability to navigate ambiguous, fast-paced work environments while managing relationships with stakeholders. Key Responsibilities: Data Engineering & Integration: Design, develop, and maintain scalable ETL/ELT pipelines using tools such as Snowflake, dbt, and Python. Build real-time and batch data processing solutions to support business analytics and operational needs. Integrate data across multiple sources (cloud and on-prem) using a variety of approaches (such as IPaaS or API-based extraction). DataOps & Infrastructure: Automate and optimize data workflows, deployment, and monitoring for reliability and performance. Implement CI/CD pipelines for data infrastructure and analytics solutions. Collaborate with IT and DevOps to maintain secure and scalable AWS-based infrastructure for data workloads. Governance & Security: Promote data quality, lineage, and governance best practices directly and through working with other teams. Work with IT and ProdSec security teams to enforce access controls and compliance requirements. Monitor and troubleshoot data infrastructure and pipeline performance using observability tools. Required Skills & Experience: 5+ years of experience in data engineering, analytics engineering, or IT infrastructure supporting data platforms. Experience with Snowflake and dbt for scalable data modeling and transformation. Hands-on experience with ETL/ELT tools (Fivetran, Census, Workato) and workflow orchestration. Strong proficiency in SQL and Python for data manipulation and automation. Familiarity with principles of IAM and Access Control. Nice-to-Have Skills: Familiarity with cloud computing providers (e.g., AWS or GCP)