Zendesk
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Overview 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. You will build and support data services and pipelines that power reporting and analytics, partnering with architects, engineers, analysts, and business stakeholders to ensure our data platforms are reliable, observable, secure, and governed.
Responsibilities
Lead data engineering projects at scale in a high visibility role working across multiple teams
Plan and deliver complex, multi-team or system projects with external dependencies
Own one or more large, mission-critical systems or multiple complex projects from design through implementation and operation
Collaborate cross-functionally to research and solve technical challenges
Design and build end-to-end analytics solutions for customer 360, finance, product, sales, and other domains; perform R&D, PoCs, and vendor evaluations
Establish engineering best practices and mentor engineers to foster technical excellence
Identify and implement internal process improvements to automate manual processes and optimize data delivery
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 experience building, operating, and maintaining scalable data platforms
4+ years of hands-on Snowflake experience with data warehouses and optimization for scalability and efficiency
5+ years of experience with cloud columnar databases (Snowflake, Google BigQuery, etc.)
3+ years of production experience with dbt and modern ELT pipelines
Experience with 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
Experience in observability, alerting, and incident management for data systems
Ability to work in a multifaceted, distributed environment
Proficiency in Python (and/or Go, Java, Scala); Python is commonly used
Excellent communication skills to collaborate with executives, data scientists, analysts, and engineers
Ability to translate business requirements into technical solutions and mentor staff to raise technical standards
What Does Our Data Stack Look Like
ELT: MySQL CDC, Kafka, Snowflake, Fivetran, dbt Core & DBT Cloud, Astronomer, Alation, Montecarlo
BI: Tableau, Looker
Infrastructure: AWS, Kubernetes, Terraform, GitHub Actions
Compensation and Work Arrangement The US annualized base salary range for this position is $183,000 - $275,000. This position may be eligible for bonus, benefits, or related incentives. Compensation is based on job-related capabilities, applicable experience, and location. The base salary excludes additional incentives where applicable. Hybrid: role requires some onsite work with flexibility to work remotely part of the week; specific in-office schedule determined by the hiring manager.
About Zendesk The Intelligent Heart Of Customer Experience. Zendesk is an equal opportunity employer. We value diversity and inclusion and do not discriminate on the basis of race, color, religion, national origin, age, sex, gender, gender identity, gender expression, sexual orientation, marital status, medical condition, disability, veteran status, or any other protected characteristic. We are AA/EEO/Veterans/Disabled. If you need accommodation during the application process, please contact us.
As part of our commitment to fairness and transparency, 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.
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Overview 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. You will build and support data services and pipelines that power reporting and analytics, partnering with architects, engineers, analysts, and business stakeholders to ensure our data platforms are reliable, observable, secure, and governed.
Responsibilities
Lead data engineering projects at scale in a high visibility role working across multiple teams
Plan and deliver complex, multi-team or system projects with external dependencies
Own one or more large, mission-critical systems or multiple complex projects from design through implementation and operation
Collaborate cross-functionally to research and solve technical challenges
Design and build end-to-end analytics solutions for customer 360, finance, product, sales, and other domains; perform R&D, PoCs, and vendor evaluations
Establish engineering best practices and mentor engineers to foster technical excellence
Identify and implement internal process improvements to automate manual processes and optimize data delivery
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 experience building, operating, and maintaining scalable data platforms
4+ years of hands-on Snowflake experience with data warehouses and optimization for scalability and efficiency
5+ years of experience with cloud columnar databases (Snowflake, Google BigQuery, etc.)
3+ years of production experience with dbt and modern ELT pipelines
Experience with 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
Experience in observability, alerting, and incident management for data systems
Ability to work in a multifaceted, distributed environment
Proficiency in Python (and/or Go, Java, Scala); Python is commonly used
Excellent communication skills to collaborate with executives, data scientists, analysts, and engineers
Ability to translate business requirements into technical solutions and mentor staff to raise technical standards
What Does Our Data Stack Look Like
ELT: MySQL CDC, Kafka, Snowflake, Fivetran, dbt Core & DBT Cloud, Astronomer, Alation, Montecarlo
BI: Tableau, Looker
Infrastructure: AWS, Kubernetes, Terraform, GitHub Actions
Compensation and Work Arrangement The US annualized base salary range for this position is $183,000 - $275,000. This position may be eligible for bonus, benefits, or related incentives. Compensation is based on job-related capabilities, applicable experience, and location. The base salary excludes additional incentives where applicable. Hybrid: role requires some onsite work with flexibility to work remotely part of the week; specific in-office schedule determined by the hiring manager.
About Zendesk The Intelligent Heart Of Customer Experience. Zendesk is an equal opportunity employer. We value diversity and inclusion and do not discriminate on the basis of race, color, religion, national origin, age, sex, gender, gender identity, gender expression, sexual orientation, marital status, medical condition, disability, veteran status, or any other protected characteristic. We are AA/EEO/Veterans/Disabled. If you need accommodation during the application process, please contact us.
As part of our commitment to fairness and transparency, 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.
#J-18808-Ljbffr