JOB DESCRIPTION

Senior Staff Data Engineer - ( This is a hybrid position, requiring candidates to reside within 50 miles of one of our hubs in San Francisco, Austin, or Madison.)
Our Enterprise Data & Analytics (EDA) is looking for an experienced Senior Staff Data Engineer to lead the design, development, and scaling of our enterprise data platform. You’ll work in a collaborative Agile environment using the latest engineering best practices with involvement in all aspects of the software development lifecycle.
As a Senior Staff Engineer on our EDA Engineering Team, you will be pivotal in building and supporting significant aspects of our data services and pipelines, that powers the next generation reporting and analytics platform. You’ll partner with architects, engineers, analysts, and business stakeholders to ensure our data platforms are reliable, observable, secure, and governed. This role is ideal for someone who thrives at the intersection of data architecture and engineering execution , influencing technical direction across multiple teams while remaining hands-on with data platforms.

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.
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

Basic Qualifications

• Bachelor’s or Master’s degree in Computer Science, Data Science, or related field.
• 10+ years of experience in data engineering, data architecture, or distributed systems , with at least 5 years in technical leadership roles.
• 7+ years of data engineering experience building, working & maintaining scalable data platforms
• 5+ years of experience with Cloud columnar databases (Snowflake, Google BigQuery etc)
• 3+ years of production experience with dbt an d modern ELT pipelines.
• Extensive experience working with various data technologies and tools such as Airflow, Snowflake, Fivetran, DBT, AWS, GitHub Actions, Docker, Kubernetes, terraform.
• Hands-on experience with AWS services (S3, Glue, EMR, Athena, Snowpipe, Kubernetes, Terraform).
• Understanding of data governance, security controls, and access management.
• Solid experience in observability, alerting, and incident management for data systems.
• Ability to work optimally in multifaceted, occasionally interrupt driven environment that includes geographically spread teams and customers
• Intermediate experience with any of the programming language: Python, Go, Java, Scala, we use primarily Python
• Excellent communication skills to collaborate with executives, data scientists, analysts, and engineers.
• Ability to work closely with data scientists, analysts, and other stakeholders to translate business requirements into technical solutions.
• Proven ability to mentor staff and senior engineers , raising the technical bar across teams

WHAT YOU GET TO DO EVERY SINGLE DAY:

• Lead data engineering projects at scale in a high visibility role working across multiple teams
• Successfully plan and deliver complex, multi-team or system, long-term projects, including ones with external dependencies
• Owns one or more large, mission-critical systems or multiple complex, team level projects, overseeing all aspects from design through implementation and operation
• Cross functional and team collaboration on researching and brainstorming different solutions for technical challenges we face
• Design and build end to end analytics solutions that provide practical insights into customer 360, finance, product, sales and other key business domains; can do critical R&D, PoC, vendor evaluation
• Establish engineering best practices and mentoring other engineers in making technical decisions on projects and foster a culture of technical excellence and continuous learning
• Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery

WHAT YOU BRING TO THE ROLE:

Basic Qualifications

• Bachelor’s or Master’s degree in Computer Science, Data Science, or related field.
• 10+ years of experience in data engineering, data architecture, or distributed systems , with at least 5 years in technical leadership roles.
• 7+ years of data engineering experience building, working & maintaining scalable data platforms
• 5+ years of experience with Cloud columnar databases (Snowflake, Google BigQuery etc)
• 3+ years of production experience with dbt an d modern ELT pipelines.
• Extensive experience working with various data technologies and tools such as Airflow, Snowflake, Fivetran, DBT, AWS, GitHub Actions, Docker, Kubernetes, terraform.
• Hands-on experience with AWS services (S3, Glue, EMR, Athena, Snowpipe, Kubernetes, Terraform).
• Understanding of data governance, security controls, and access management.
• Solid experience in observability, alerting, and incident management for data systems.
• Ability to work optimally in multifaceted, occasionally interrupt driven environment that includes geographically spread teams and customers
• Intermediate experience with any of the programming language: Python, Go, Java, Scala, we use primarily Python
• Excellent communication skills to collaborate with executives, data scientists, analysts, and engineers.
• Ability to work closely with data scientists, analysts, and other stakeholders to translate business requirements into technical solutions.
• Proven ability to mentor staff and senior engineers , raising the technical bar across teams.