Job Description
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 that the rest of the analytics organisation also depends on for support-operations insight, and product decision-making. Our data assets serve external customers and internal stakeholders in equal measure, but the customer-facing surface is where the quality bar is set.
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. You will work across code, dbt models, and datasets, helping teams build and improve the data assets behind Zendesk's customer-facing reporting.
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. 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 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
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.
