Senior Data Engineer
Zendesk3 Locations$151k – $227kPosted 27 March 2026
Tech Stack
Job Description
Job Description
Our Enterprise Data & Analytics (EDA) is looking for an experienced Senior Data Engineer to join our growing data engineering team. You’ll work in a collaborative Agile environment using the latest engineering best practices with involvement in all aspects of the software development lifecycle.
You will craft and develop curated data products, applying standard architectural & data modeling practices to maintain the foundation data layer serving as a single source of truth across Zendesk . You will be primarily developing Data Warehouse Solutions in BigQuery/Snowflake using technologies such as dbt, Airflow, Terraform.
What you get to do every single day:
Collaborate with team members and business partners to collect business requirements, define successful analytics outcomes and design data models
Serve as Data Model subject matter expert and data model spokesperson, demonstrated by the ability to address questions quickly and accurately
Implement Enterprise Data Warehouse by transforming raw data into schemas and data models for various business domains using SQL & dbt
Design, build, and maintain ELT pipelines in Enterprise Data Warehouse to ensure reliable business reporting using Airflow, Fivetran & dbt
Optimize data warehousing processes by refining naming conventions, enhancing data modeling, and implementing best practices for data quality testing
Build analytics solutions that provide practical insights into customer 360, finance, product, sales and other key business domains
Build and Promote best engineering practices in areas of version control system, CI/CD, code review, pair programming
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
5 years of data engineering experience building, working & maintaining data pipelines & ETL processes on big data environments
5 years of experience in Data Modeling and Data Architecture in a production environment
5 years in writing complex SQL queries
5 years of experience with Cloud columnar databases (We use Snowflake)
2 years of production experience working with dbt and designing and implementing Data Warehouse solutions
Ability to work closely with data scientists, analysts, and other stakeholders to translate business requirements into technical solutions. Strong documentation skills for pipeline design and data flow diagrams.
Intermediate experience with any of the programming language: Python, Go, Java, Scala, we primarily use Python
Integration with 3rd party API SaaS applications like Salesforce, Zuora, etc
Ensure data integrity and accuracy by conducting regular data audits, identifying and resolving data quality issues, and implementing data governance best practices.
Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
Preferred Qualifications
Hands-on experience with Snowflake data platform, including administration, SQL scripting, and query performance tuning
Good Knowledge in modern as well as classic Data Modeling - Kimball, Innmon, etc
Demonstrated experience in one or many business domains (Finance, Sales, Marketing)
3 completed “production-grade” projects with dbt
Expert knowledge in python
What does our data stack looks like:
ELT (Snowflake, Fivetran, dbt, Airflow, Kafka, HighTouch)
BI (Tableau, Looker)
Infrastructure (GCP, AWS, Kubernetes, Terraform, Github Actions)
The US annualized base salary range for this position is $151,000.00-$227,000.00. 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 ... (truncated, view full listing at source)
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