Staff Data Engineer

Das ist der Job

You will craft and develop curated datasets, applying standard architectural & data modeling practices.

Darum lohnt es sich

The ‘Zendesk Analytics Prototyping’ (ZAP) team is looking for an experienced Staff Data Engineer to support the team’s charter to accelerate CRM measurements and insights, and help promote a data-centric approach to improving customer support tools and operations.

The role will be responsible for closely partnering with Software Development Engineers and Business Intelligence Engineers to build high quality data pipelines and manage the team’s data lake.

What you’ll be doing: Collaborate with team members and internal stakeholders to understand business requirements, define successful analytics outcomes, and design data models. Hands‑on production experience with dbt, and proven knowledge in modern and classic Data Modeling – Kimball, Inmon, etc.

To realize that mission, we build and maintain robust, fine-grained, and contextually rich datasets, providing a foundation for developing insights that help enhance Zendesk’s support operations.

You’ll work in a collaborative environment using the latest engineering best practices with involvement in all aspects of the software development lifecycle. You will be primarily developing Data Warehouse Solutions in Snowflake using technologies such as dbt, Airflow, Terraform.

Develop, automate, and maintain scalable ELT pipelines in our Data Warehouse, ensuring reliable business reporting. Design & build ELT based data models using SQL & DBT. Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery.

Work with data and analytics experts to strive for greater functionality in our data systems. What you bring to the role Basic Qualifications 8+ 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. Proficiency in a programming language such as Python, Go, Java, or Scala. Experience with cloud columnar databases (Google BigQuery, Amazon Redshift, Snowflake), query authoring (SQL) as well as working familiarity with a variety of databases.

Experience with processes supporting data transformation, data structures, metadata, dependency, ensuring efficient data processing performance and workload management. Excellent communication and collaboration skills. Thrives in ambiguous situations, possesses a proactive problem‑solving attitude.

Preferred Qualifications Experience with BigQuery, Snowflake, or similar cloud warehouses. Familiarity with AI tools and techniques that could be applied to data analysis and data transformation tasks. Completed projects with dbt. Familiarity with Lean/6 Sigma principles and an understanding of CRM analytics.

Our Data Stack ELT (Snowflake, dbt, Airflow, Kafka) BI (Tableau, Looker) Infrastructure (AWS, Kubernetes, Terraform, GitHub Actions) #J-18808-Ljbffr