Description
Zendesk's mission is to make Customer Experience better - for every brand, every customer, every day.
The Zendesk Analytics Prototyping (ZAP) team designs and ships fine-grained, contextually rich datasets that power Zendesk's customer-facing analytics application.
We're looking for a Senior AI Data Engineer to join our team, with strong data engineering experience and a keen interest in applying AI-related tools and practices in practical ways.
What you'll be doing:
- 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.
What you bring to the role
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.
- 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 the discipline of 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/6 Sigma principles and an understanding of CRM analytics.
Our Data Stack: ELT: Snowflake, dbt, Airflow, Kafka BI: Zendesk proprietary application, Looker Infrastructure: AWS, Kubernetes, Terraform, GitHub Actions