Job Description About us We are looking for a Senior Data Engineer to support the Foundation Insights team. You will work cross-functionally to help drive analytics, enablement, and data-driven decision-making for our global engineering and product teams. Foundation Insights at Zendesk owns operational data for Engineering and Product Development — measuring productivity, reliability, AI adoption, and infrastructure excellence. As a Senior Data Engineer, your role will be designing, building, testing, and maintaining highly scalable data pipelines and analytical data models. You will ensure that systems meet business requirements and industry practices, and you'll have the opportunity to work with many datasets and tools such as GitHub, Jira, Snowflake, dbt, and AI platforms like Claude and MCP servers, among others. Your responsibilities will include building dimensional models, integrating data sources, optimizing performance, and developing self-service data products. Your contributions will play a significant role in shaping our engineering data strategy and will directly impact decision-making capabilities throughout all of Product Development. What you'll do: Design and build dimensional data models using dbt in Snowflake Develop and maintain ETL pipelines and Airflow DAGs to centralize engineering operational metrics across multiple Snowflake accounts Build self-service data products including Django-based dashboards, MCP servers for AI-powered data exploration, and interactive analytics applications Build data models to track platform adoption, AI tool usage, and ROI across engineering. Optimize data product performance through query optimization, pre-aggregated models, and caching strategies to improve dashboard and API response times Implement data quality tests, monitoring, and validation layers to ensure accuracy and prevent invalid metric comparisons Integrate data from APIs and third-party tools into Snowflake for analytics and AI enrichment Use best engineering practices such as CI/CD, infrastructure-as-code, code review, comprehensive testing, and documentation Collaborate with Engineering, Product, and leadership to measure infrastructure adoption, AI ROI, and engineering productivity What you bring to the role: Basic Qualifications: 3-5+ years of data engineering experience building, maintaining, and optimizing production data pipelines and analytical data models Proven proficiency in Python and SQL — comfortable with complex queries, ETL development, and application development (Django/Flask) Hands-on dbt experience — building dimensional models, writing tests, managing dependencies, and optimizing performance Experience with cloud data warehouses (Ex. Snowflake, BigQuery, Redshift, Databricks) including query optimization and cost management Internally motivated, self-starter with strong analytical thinking — you dig into data anomalies and ask "why" until you understand root causes Ability to work cross-functionally and communicate technical concepts to both engineers and non-technical stakeholders Detail-oriented with a passion for data quality, testing, and building reliable production systems Preferred Qualifications: Data orchestration with Airflow — building DAGs, managing dependencies, and monitoring pipeline health Proficiency in infrastructure-as-code practices, particularly using Terraform for managing Snowflake and cloud resources Web development with Django, Flask, or similar Python frameworks for building data applications LLM/AI integration experience — working with Claude, GPT, or other AI APIs; building MCP servers or AI agent frameworks Experience integrating and ingesting data from third-party APIs and external platforms Background working with large datasets, data quality monitoring tools (Monte Carlo, dbt tests), and observability platforms (Datadog, Splunk) Knowledge of engineering productivity metrics, DORA metrics, PR review cycles, deployment frequency, incident management KPIs Familiarity with containerization technologies and CI/CD automation The intelligent heart of customer experience Zendesk software was built to bring a sense of calm to the chaotic world of customer service. Today we power billions of conversations with brands you know and love. Zendesk believes in offering our people a fulfilling and inclusive experience. Our hybrid way of working, enables us to purposefully come together in person, at one of our many Zendesk offices around the world, to connect, collaborate and learn whilst also giving our people the flexibility to work remotely for part of the week. As part of our commitment to fairness and transparency, we inform all applicants that artificial intelligence (AI) or automated decision systems may be used to screen or evaluate applications for this position, in accordance with Company guidelines and applicable law. Zendesk is an equal opportunity employer, and we’re proud of our ongoing efforts to foster global diversity, equity, & inclusion in the workplace. Individuals seeking employment and employees at Zendesk are considered without regard to race, color, religion, national origin, age, sex, gender, gender identity, gender expression, sexual orientation, marital status, medical condition, ancestry, disability, military or veteran status, or any other characteristic protected by applicable law. We are an AA/EEO/Veterans/Disabled employer. If you are based in the United States and would like more information about your EEO rights under the law, please click here. Zendesk endeavors to make reasonable accommodations for applicants with disabilities and disabled veterans pursuant to applicable federal and state law. If you are an individual with a disability and require a reasonable accommodation to submit this application, complete any pre-employment testing, or otherwise participate in the employee selection process, please send an e-mail to peopleandplaces@zendesk.com with your specific accommodation request.