Senior AI Data Engineer
AI in this role
Job Description
Job DescriptionZendesk'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.
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.
How we rate this
Senior AI Data Engineer at Zendesk rates 7 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.
Little AI. AI is not part of the work.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
Prepare for this job
A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.
Skills and AI tools this role asks for
Questions you could be asked
- What's a project where you used Claude hands-on?
- Walk me through how you've used Cursor in your day-to-day work.
- What are the limits of Claude Code that you've run into, and how did you work around them?
Adapt your resume
- List these exact terms on your resume: Claude, Cursor, and Claude Code. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
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