Senior Staff Data Engineer

Zendesk, Inc.; Madison (WI); Hybrid; USD 200,000 - 300,000; Full time

Job summary

Zendesk, Inc. is seeking a Senior Staff Engineer to lead the architecture and engineering of an AI-ready semantic data platform.

You will shape the enterprise semantic layer across metrics, dimensions, and relationships to enable analytics and AI agents with a trusted data foundation. You will partner with data engineers, data scientists, and AI teams to define reusable capabilities, ensure governance, and deliver production-ready solutions.

Qualifications

• Bachelor's or Master's degree in Computer Science, Data Engineering, Data Science, or related field.
• 10+ years of experience in data engineering, data architecture, distributed systems, software engineering, or related platform disciplines with technical leadership.
• At least 3+ years of hands-on experience in Semantic Layer implementation.
• Experience designing and building large-scale data/analytics/semantic/platform systems in production.
• Deep expertise with Snowflake or Databricks, dbt, and cloud-based ELT pipelines.
• Strong software engineering fundamentals with SQL and Python/Java/Go/Scala.
• Understanding of dimensional, entity-based data modeling and metrics definitions.
• Excellent communication and ability to collaborate with executives and engineers.
• Proven ability to mentor senior engineers and influence decisions across teams.

Responsibilities

• Define enterprise semantic architecture for metrics, dimensions, entities, relationships, grain, time semantics, and business context.
• Establish reusable semantic contracts for consistent business definitions and data products.
• Evaluate and recommend long-term semantic platform architecture (Snowflake, dbt, Cube, etc.).
• Design and build metadata-driven platform capabilities for semantic discovery and governance.
• Define how conversational analytics consume enterprise semantics and interact with Data Agents.
• Establish golden datasets and evaluation practices for semantic interpretation and metric correctness.
• Lead multi-team initiatives from architecture to production adoption and improvement.
• Influence build-vs-buy decisions; mentor engineers across Data Eng, Analytics, BI, and AI.
• Treat platform as internal product with documentation, onboarding, and migration efforts.

Skills

Technical leadership

Data architecture

Data engineering

SQL

Programming (Python/Java/Go/Scala)

Communication

Mentoring

Cross-team collaboration

Architectural direction

Education

Bachelor's or Master's in CS/Data Science/Data Engineering

Tools

Snowflake Semantic Views

dbt

dbt Semantic Layer / MetricFlow

Cube

LookML / Looker

Atscale

Job description

Job Description

Enterprise Semantic Layer

Our Enterprise Data & Analytics (EDA) team is looking for an experienced Senior Staff Engineer to lead the architecture and engineering of an Enterprise AI-ready semantic data platform. We are building an AI-ready Enterprise data foundation that enables analytics, applications, and AI agents to operate from the same trusted understanding of business data.

Our platform includes trusted foundational data models across Customer, Finance, GTM, and Product; a governed semantic layer for metrics, dimensions, entities, relationships, and business context; and conversational analytics over enterprise data.

As a Senior Staff Engineer on our EDA Engineering Team, this role sits at the intersection of data engineering, data architecture, software engineering, and AI. The successful candidate will partner with architects, data engineers, data scientists, Analysts Teams, and AI teams to establish reusable platform capabilities that are reliable, observable, secure, governed, and practical to adopt. This role is ideal for someone who can set technical direction across multiple teams while remaining hands-on with architecture, prototyping, and production delivery.

What You Get To Do Every Single Day

• Define the enterprise semantic architecture for metrics, dimensions, entities, relationships, grain, time semantics, and business context over trusted foundational data models.
• Establish reusable semantic contracts so analytics, applications, and AI systems operate from consistent business definitions and governed data products.
• Evaluate and recommend the long-term semantic platform architecture, including Snowflake Semantic Views, dbt Semantic Layer / MetricFlow, Cube, and other approaches.
• Design and build metadata-driven platform capabilities for semantic discovery, deterministic metric computation, query generation, governed access, versioning, and extensibility.
• Define how conversational analytics systems consume enterprise semantics and structured data, partnering with AI teams on building Data Agents and other AI interfaces.
• Establish golden datasets and evaluation practices for semantic interpretation, generated-query accuracy, metric correctness, and analytical answer quality.
• Lead complex, multi-team initiatives from architecture and proof of concept through production adoption, operational support, and continuous improvement.
• Influence build-versus-buy decisions, mentor engineers, and raise the technical bar across Data Engineering, Analytics, BI, and AI.
• Treat the platform as an internal product by improving contributor experience, documentation, onboarding, adoption, and migration from duplicate implementations.

Basic Qualifications

What you bring to the role:

• Bachelor's or Master's degree in Computer Science, Data Engineering, Data Science, or a related field, or equivalent practical experience.
• 10+ years of experience in data engineering, data architecture, distributed systems, software engineering, or related platform disciplines, with significant technical leadership experience.
• At least 3+ years of hands on experience in Semantic Layer implementation
• Demonstrated experience designing and building large-scale data, analytics, semantic, developer, or platform systems used by multiple teams. (ex. Atscale, Cube.dev, DBT Metric Flow, etc.) in production environments
• Deep expertise with modern analytical warehouses and transformation frameworks, including Snowflake or Databricks, dbt, and cloud-based ELT pipelines.
• Strong software engineering fundamentals and production experience with SQL and at least one programming language such as Python, Java, Go, Scala, or similar.
• Deep understanding of dimensional, entity-based, and analytical data modeling, including grain, relationships, time dimensions, and metric definitions.
• Excellent communication skills and the ability to collaborate with executives, architects, engineers, analysts, data scientists, and business stakeholders.
• Proven ability to mentor senior engineers and influence technical decisions across multiple teams.

Preferred Experience

• Experience with one or more of Snowflake Semantic Views, dbt Semantic Layer / MetricFlow, Cube, LookML / Looker, or comparable semantic and metrics platforms.
• Experience with text-to-SQL, agent evaluation, MCP, or conversational analytics.
• Experience defining deterministic boundaries between governed metric computation and probabilistic AI reasoning.
• Experience evaluating vendors or open-source platforms and translating architectural recommendations into an adoption roadmap.

What Does Our Data Stack Looks Like

• ELT (MYSQL CDC, Kafka, Snowflake, Fivetran, dbt Core & DBT Cloud, Astronomer, Alation, Montecarlo)
• BI (Tableau, Looker)
• Infrastructure (AWS, Kubernetes, Terraform, Github Actions)

The US annualized base salary range for this position is $200,000.00-$300,000.00. This position may also be eligible for bonus, benefits, or related incentives. While this range reflects the minimum and maximum value for new hire salaries for the position across all US locations, the offer for the successful candidate for this position will be based on job related capabilities, applicable experience, and other factors such as work location. Please note that the compensation details listed in US role postings reflect the base salary only (or OTE for commissions based roles), and do not include bonus, benefits, or related incentives.

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 [e-mail] with your specific accommodation request.