Senior AI Data Engineer

Overview

Zendesk's mission is to make Customer Experience better - for every brand, every customer, every day. Data and analytics are the engine of that vision: the vehicle through which we deliver actionable insights to the 125,000+ global brands that run on Zendesk, and to the internal teams who build the next generation of CX products on top of that data. The Zendesk Analytics Prototyping (ZAP) team sits at the sharp end of that mission. We design and ship the fine grained, contextually rich datasets that power Zendesk's customer facing analytics application, and the rest of the analytics organization also relies on those data assets for support operations insight and product decision making.

Responsibilities

• Develop and maintain ELT pipelines, ensuring data reliability and scalability for business reporting and analytics use cases.
• Build and optimize SQL based data models using dbt and other ETL tools.
• Support ZAP's progress toward a more AI enabled operating model, using emerging technologies to help improve team productivity.
• Identify and implement improvements in data delivery, processing performance, and system efficiency.
• Collaborate with team members to define requirements and translate them into scalable data models and pipelines.
• Contribute to the team's technical vision and bring innovative solutions to enhance data systems.

Basic Qualifications

• 5+ years of data engineering experience building, maintaining and working with data pipelines & ETL processes in big data environments.
• Extensive experience with SQL, ideally in the context of data modeling and analysis.
• Hands on production experience with dbt, and proven knowledge in modern and classic Data Modeling - Kimball, Inmon, etc.
• Programming skills in Python or a similar language, with an emphasis on data transformation and automation.
• Experience with cloud columnar databases (Google BigQuery, Amazon Redshift, Snowflake), query authoring (SQL) as well as working familiarity with a variety of databases.
• Proven experience in performance testing, capacity planning, and cost optimization for large scale, complex data pipelines and systems. This includes identifying bottlenecks, ensuring scalability, and minimizing operational costs in cloud based data environments.
• Excellent communication and collaboration skills.

Preferred Qualifications

• Experience building or operating an AI augmented engineering practice - agentic IDE workflows (Cursor, Claude Code), prompt/skill engineering, eval design, and treating AI artefacts as production code.
• SnowPro Core certification or equivalent hands on expertise.
• Hands on production experience with Apache Spark (Spark SQL / PySpark).
• Familiarity with Lean/6Sigma principles and an understanding of CRM analytics.

Data Stack

• ELT: Snowflake, dbt, Airflow, Kafka.
• BI: Zendesk proprietary application, Looker.
• Infrastructure: AWS, Kubernetes, Terraform, GitHub Actions.

Equal Opportunity Statement

Zendesk is an equal opportunity employer and we're proud of our ongoing efforts to foster global diversity, equity, and 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 contact the appropriate office. Zendesk endeavors to make reasonable accommodations for applicants with disabilities and disabled veterans pursuant to applicable federal and state law.