Senior IT DataOps Business Intelligence Engineer, Gong

• You are a strong self-starter with the ability to navigate ambiguous, fast-paced work environments while managing stakeholder relationships
• 2-5 years of experience in BI Engineering, analytics engineering, or IT infrastructure supporting data platforms
• Experience with Snowflake, GitHub, and dbt for scalable data modeling and transformation
• Hands-on experience with ETL/ELT tools (Fivetran, Census, and Workato) and workflow orchestration
• Strong proficiency in SQL and Python for data manipulation and automation
• Experience with ad hoc analytics to support customer reporting requests
• Familiarity with principles of IAM and Access Control
• AI/LLM Integration Experience: Familiarity with integrating REST APIs for Large Language Models (LLMs) into data pipelines or front-end tools (Retool)

Desirable

• As an IT DataOps 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 own 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
• A major focus of this role will be administering our Tableau environments (Server & Cloud), developing and administration of internal operational tools via Retool, and driving our Reverse ETL (RETL) strategy
• Additionally, you will play a key role in operationalizing AI-driven insights—building pipelines that deliver predictive metrics and LLM-generated data points directly into our core business applications
• We are looking for an IT DataOps Business Intelligence 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, Census, Tableau, and Workato—to ensure data flows efficiently and securely across the organization
• Reverse ETL (RETL) & Data Activation: Design, develop, and own scalable RETL pipelines using Census, Workato, dbt, and Snowflake
• Operational Integration: Map transformed data models into destination SaaS applications (e.g., Salesforce, Zendesk), managing API rate limits, webhook handling, data sync observability, and error resolution
• Integrate data across multiple sources (cloud and on-prem) using a variety of approaches (such as IPaaS or API-based extraction)
• Tableau Administration & Architecture: Manage, optimize, and scale Tableau Server and Tableau Cloud environments. Handle user provisioning, security/permissions, site administration, extract scheduling, and performance tuning
• Retool Application Development: Partner with business teams to architect, build, and maintain custom internal applications in Retool. Integrate Retool with Snowflake, REST APIs, and third-party systems to create actionable user interfaces
• Platform Governance: Establish best practices for dashboard deployment, Retool app lifecycle management, and BI environment stability
• AI Tooling Integration: Integrate Generative AI APIs (e.g., OpenAI, Anthropic, Vertex AI) or Retool's native AI components into internal applications to automate workflows, summarize data, or create smart conversational interfaces for business users
• Modern BI & AI Features: Pilot and implement emerging AI features within our BI stack, to enhance self-service analytics
• 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
• 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
• Monitor system access and data integrity with tools like Cyera and Seemoredata