Sr. Manager, Data Engineering at Vail Resorts Corporate
British Columbia, British Columbia, Canada -
Full Time


Start Date

Immediate

Expiry Date

15 Nov, 25

Salary

117000.0

Posted On

15 Aug, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Data Engineering, Sql, Data Architecture, Computer Science, Kubernetes, Docker, Interpersonal Skills, Cloud, Python, Git, Devops

Industry

Information Technology/IT

Description

Our mission is to create the Experience of a Lifetime for our employees, so they can, in turn, create the Experience of a Lifetime for our guests. We own and operate the most renowned destination resorts in the world as well as regional and local ski areas outside major cities, and connect them all through one unrivaled network. We are looking for ambitious leaders, innovators and creators to join our talented team. If you’re ready to pursue your fullest potential, we want to get to know you!
Candidates for year-round positions are reviewed on a rolling basis. Applications will be accepted up to 90 days after the posting date, or until the position is filled (whichever is first).

JOB SUMMARY:

As a Sr. Manager, Data Engineering at Vail Resorts, you will be responsible for leading and managing a team of Data Engineers to ensure the efficient and effective delivery of data pipelines. You will oversee the design, implementation, and maintenance of data pipelines, ensuring seamless collaboration and automation across our development teams and QE teams. Your expertise will be instrumental in implementation and optimization of our data infrastructure and application pipelines, automated QE framework, resulting in accelerated time-to-value.

JOB REQUIREMENTS:

  • Bachelor’s degree in Computer Science, Data Engineering, or a related engineering field
  • 8+ years of experience in data engineering
  • 5+ years of experience leading and managing technical teams
  • 5+ years of experience working with Git or similar CI/CD tools
  • Strong proficiency in configuration languages (Terraform, YAML)
  • Strong proficiency in Python, PySpark, SQL
  • Experience with data engineering tools and frameworks (Delta Lake, DataBricks, SQL)
  • Experience with containerization tools like Docker and Kubernetes
  • In-depth knowledge of DevOps and its capabilities for data engineering
  • Strong understanding of data engineering principles and practices
  • Experience with Databricks and its capabilities for data engineering
  • Experience with Event based architecture implementation
  • Experience with cloud computing concepts and Azure services
  • Familiarity with data quality and validation tools
  • Excellent communication and interpersonal skills
  • Strong leadership and organizational skills
  • Ability to drive results and meet deadlines

PREFERRED QUALIFICATIONS:

  • Knowledge of cloud data architecture and data management principles
  • Certification in Azure DevOps, Databricks, Terraform, or related technologies
    The expected Total Compensation for this role is $117.000 - $157,000 + annual bonus. Individual compensation decisions are based on a variety of factors.
Responsibilities

Job Responsibilities:

  • Lead and manage a team of Data Engineers responsible for data pipeline automation
  • Define and implement strategies and best practices for data engineering
  • Oversee design, implementation, and maintenance of code pipelines for platform infrastructure and application ex: data ingestion, transformation, and delivery
  • Collaborate with DevOps team and other stakeholders to understand requirements and translate them into effective CI/CD solutions
  • Ensure the effective integration of Databricks notebooks and workflows into DevOps pipelines
  • Integrate with external APIs and services (e.g., RESTful APIs) to exchange data and trigger actions
  • Design and Develop data APIs and API Management layer
  • Implement and maintain infrastructure as code (IaC) using tools like Terraform or Ansible
  • Participate in code reviews and contribute to the improvement of development processes
  • Monitor and optimize the performance of pipelines and environments
  • Oversee and assist troubleshooting and resolution of issues related to data pipelines and DevOps
  • Stay up-to-date with the latest data pipeline features, Databricks capabilities, and best practices for data engineering
  • Mentor and guide team members in data engineering and DevOps practices
  • Foster a culture of innovation, collaboration, and continuous improvement within the tea

Full Time roles are eligible for the above, plus:

  • Health Insurance; Medical Insurance, Dental Insurance, and Vision Insurance plans (for eligible seasonal employees after working 500 hours)
  • Free ski passes for dependents
  • Critical Illness and Accident plan
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