Zendesk
Senior Staff Data Engineer – Zendesk
Zendesk
is seeking an experienced
Senior Staff Data Engineer
to lead the design, development, and scaling of our enterprise data platform within the Enterprise Data & Analytics (EDA) team. The role is fully integrated in a collaborative Agile environment, using modern engineering best practices across the entire software development lifecycle.
Job Overview As a pivotal member of the EDA Engineering team, you will build and support the next‑generation reporting and analytics platform. You will partner with architects, engineers, analysts, and business stakeholders to ensure our data platforms are reliable, observable, secure, and governed. This is an ideal fit 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.
Responsibilities
Lead data engineering projects at scale in a high‑visibility role across multiple teams.
Plan and deliver complex, multi‑team, long‑term projects, including those with external dependencies.
Own one or more large, mission‑critical systems or multiple complex, team‑level projects, overseeing all aspects from design through implementation and operation.
Cross‑functional collaboration on researching and brainstorming solutions for technical challenges.
Design and build end‑to‑end analytics solutions that provide practical insights into key business domains (customer 360, finance, product, sales, etc.).
Establish engineering best practices, mentor other engineers, and foster a culture of technical excellence and continuous learning.
Identify, design, and implement internal process improvements to automate manual processes and optimize data delivery.
Basic Qualifications
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, and maintaining scalable data platforms.
4+ years of hands‑on Snowflake experience, including designing and managing data warehouses, optimizing performance and costs, migrating data, and implementing best practices for scalability.
5+ years of experience with cloud columnar databases (Snowflake, Google BigQuery, etc.).
3+ years of production experience with dbt and modern ELT pipelines.
Extensive experience with tools such as Airflow, Fivetran, DBT, AWS S3/Glue/EMR/Athena, Kubernetes, Terraform, GitHub Actions, Docker.
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 a multifaceted, interrupt‑driven environment with geographically spread teams and customers.
Intermediate experience with Python, Go, Java, or Scala (primarily Python).
Excellent communication skills to collaborate with executives, data scientists, analysts, and engineers.
Proven ability to mentor staff and senior engineers, raising the technical bar across teams.
Data Stack
ELT: MySQL CDC, Kafka, Snowflake, Fivetran, dbt Core & dbt Cloud, Astronomer, Alation, Monte Carlo.
BI: Tableau, Looker.
Infrastructure: AWS, Kubernetes, Terraform, GitHub Actions.
Base Salary : US $183,000–$275,000 annually (plus potential bonus, benefits, or related incentives). Salary will be determined based on job‑related capabilities, experience, and location factors.
Hybrid Work : This role requires regular onsite attendance at a local office part of the week, with flexibility to work remotely for the remaining days.
Zendesk believes in offering a fulfilling and inclusive experience. Our hybrid way of working enables purposeful in‑person collaboration while providing flexibility to work remotely as needed.
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. We are proud of our ongoing efforts to foster diversity, equity, and inclusion. All applicants and employees are considered without regard to race, color, religion, national origin, age, sex, gender identity, sexual orientation, marital status, disability, military or veteran status, or any other characteristic protected by law. If you are a U.S. applicant, you can find your EEO rights here. Reasonable accommodations for applicants with disabilities are provided upon request.
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is seeking an experienced
Senior Staff Data Engineer
to lead the design, development, and scaling of our enterprise data platform within the Enterprise Data & Analytics (EDA) team. The role is fully integrated in a collaborative Agile environment, using modern engineering best practices across the entire software development lifecycle.
Job Overview As a pivotal member of the EDA Engineering team, you will build and support the next‑generation reporting and analytics platform. You will partner with architects, engineers, analysts, and business stakeholders to ensure our data platforms are reliable, observable, secure, and governed. This is an ideal fit 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.
Responsibilities
Lead data engineering projects at scale in a high‑visibility role across multiple teams.
Plan and deliver complex, multi‑team, long‑term projects, including those with external dependencies.
Own one or more large, mission‑critical systems or multiple complex, team‑level projects, overseeing all aspects from design through implementation and operation.
Cross‑functional collaboration on researching and brainstorming solutions for technical challenges.
Design and build end‑to‑end analytics solutions that provide practical insights into key business domains (customer 360, finance, product, sales, etc.).
Establish engineering best practices, mentor other engineers, and foster a culture of technical excellence and continuous learning.
Identify, design, and implement internal process improvements to automate manual processes and optimize data delivery.
Basic Qualifications
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, and maintaining scalable data platforms.
4+ years of hands‑on Snowflake experience, including designing and managing data warehouses, optimizing performance and costs, migrating data, and implementing best practices for scalability.
5+ years of experience with cloud columnar databases (Snowflake, Google BigQuery, etc.).
3+ years of production experience with dbt and modern ELT pipelines.
Extensive experience with tools such as Airflow, Fivetran, DBT, AWS S3/Glue/EMR/Athena, Kubernetes, Terraform, GitHub Actions, Docker.
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 a multifaceted, interrupt‑driven environment with geographically spread teams and customers.
Intermediate experience with Python, Go, Java, or Scala (primarily Python).
Excellent communication skills to collaborate with executives, data scientists, analysts, and engineers.
Proven ability to mentor staff and senior engineers, raising the technical bar across teams.
Data Stack
ELT: MySQL CDC, Kafka, Snowflake, Fivetran, dbt Core & dbt Cloud, Astronomer, Alation, Monte Carlo.
BI: Tableau, Looker.
Infrastructure: AWS, Kubernetes, Terraform, GitHub Actions.
Base Salary : US $183,000–$275,000 annually (plus potential bonus, benefits, or related incentives). Salary will be determined based on job‑related capabilities, experience, and location factors.
Hybrid Work : This role requires regular onsite attendance at a local office part of the week, with flexibility to work remotely for the remaining days.
Zendesk believes in offering a fulfilling and inclusive experience. Our hybrid way of working enables purposeful in‑person collaboration while providing flexibility to work remotely as needed.
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. We are proud of our ongoing efforts to foster diversity, equity, and inclusion. All applicants and employees are considered without regard to race, color, religion, national origin, age, sex, gender identity, sexual orientation, marital status, disability, military or veteran status, or any other characteristic protected by law. If you are a U.S. applicant, you can find your EEO rights here. Reasonable accommodations for applicants with disabilities are provided upon request.
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