Job description

At YETI, we believe that time spent outdoors matters more than ever and our gear can make that time extraordinary. When you work here, you’ll have the opportunity to create exceptional, meaningful work and problem solve with innovative team members by your side. Together, you’ll help our customers get the high-quality gear they need to make the most of their adventures. We are BUILT FOR THE WILD™. About the Role We are actively searching for a Senior Director, Enterprise Integrations and Data Engineering to oversee YETI’s Data Warehouse, Analytics Platforms, MDM, and Integration Platforms. This role is responsible for defining and executing YETI’s enterprise data, analytics, master data management (MDM), and integration strategy. This leader will oversee the platforms, architecture, governance, and engineering capabilities that enable reliable, scalable, and secure data movement across the organization. Partnering closely with business and technology leaders, the Senior Director will drive modernization of YETI’s data ecosystem, ensuring the company can leverage trusted data, advanced analytics, automation, AI, and machine learning to accelerate growth and improve decision-making. This role is accountable for the performance and evolution of the enterprise data warehouse, analytics platforms, integration services, and API strategy, while building and leading high-performing teams and strategic vendor partnerships to deliver business value at scale. What You ll Do Work cross-functionally across engineering, product, sales, and various other teams in support of successful implementations. Modernize core data infrastructure and data sets to support planned business growth. Gather business and functional requirements and translate these requirements into robust, scalable, operable solutions with a flexible and adaptable data architecture. Lead and manage end to end cloud native data platform/data warehouse solutions, provide data and capabilities that are scalable for Data Products & AI/ML Solutions for the enterprise and ensuring the architecture is optimized to meet the requirements and needs of the business. Provide the necessary tools, technologies, data architectures and data stewardship to allow the organization to leverage analytics for making business decisions with both structured and unstructured data, while managing quality, data accuracy and security. Identify, design, and implement engineering process improvements through automating manual processes, optimizing data pipelines, re-designing services for greater scalability. Collaborate with BI Engineers, Software Engineers, Data Scientists and other business stakeholders to deliver high quality data architecture and pipelines. Provide strategy and tools necessary for data exploration, reporting and ability to move towards Artificial Intelligence (AI) and Machine Learning (ML) models. Establish and maintain best practices, standards, and governance for data quality, security, privacy, and compliance across the analytics platform and services. Develop and implement Enterprise Integration strategy, lead the implementation of a scalable API first integration platform. Lead enterprise integrations capabilities covering all data movement across supply chain, merchandising, finance, store, ecommerce, HR, etc. Hire and lead a team of data engineers and analytics professionals. Develop and execute strategies for maintaining and enhancing our enterprise data solutions, including networks, servers, storage, and cloud services. Build the frameworks required for optimal extraction, transformation, and loading of data from a wide variety of data sources using GCP technologies. Build analytics tools that utilize the data pipeline to provide actionable insights and integrate insights with various consumer touchpoints. Oversight of managed services contract for the run and maintain of the data warehouse, analytics platform and services, ensuring service level agreements and quality standards. Collaborate with vendors and partners to optimize technology solutions. Collaborate with cross-functional teams to ensure seamless equipment lifecycle processes. What You Bring Bachelor’s degree required Greater than 15 years of experience in Technology roles, with extensive experience in data engineering and integrations, or equivalent combination of education and experience Greater than 10 years of people management experience, managing both internal and external (contract) resources of varying seniority At least 5 years demonstrated leadership experience in complex business and technical environments, specifically in developing and maintaining large analytical data warehouses (BI/Big data) and a leader in technical problem solving and data integration tools Experience with API Intergration platforms and data movement platforms, Mulesoft, Boomi, Apigee, Google Cloud Platform or other cloud technologies, BigQuery, Databricks, Business Objects, Tableau, Power BI, and other emerging big data technologies. Strong understanding of next gen data practices (e.g., MLOps, Data Ops, Data Science) and experience applying them in an enterprise organization. Fluent in data technologies such as data governance tooling, data platform technologies, and enterprise/data architecture principles. Analytical mindset for addressing complex challenges Passion for building outstanding teams and creating an environment where individuals can do their best work Executive presence and the ability to effectively communicate across varying audiences Strong business and commercial acumen #LI-AR2 Benefits & Perks: Click here to learn about the benefits and perks we offer at YETI. YETI is proud to be an Equal Opportunity Employer. Our commitment to creating a diverse, equitable, and inclusive culture is at the center of everything we do for our employees. We embrace all applicants looking to bring their authentic selves to YETI and contribute to our mission of keeping the wild WILD. Find out more about our commitment to DE&I at yeti.com/esg.html. All applicants for employment will be considered without regard to an individual’s race, color, sex, gender identity, gender expression, religion, age, national origin or ancestry, citizenship, physical or mental disability, medical condition, family care status, marital status, sexual orientation, genetic information, military or veteran status, or any other basis protected by federal, state or local laws. YETI Applicant Privacy Notice YETI welcomes and encourages applications from people with disabilities. Accommodations are available upon request for candidates taking part in all aspects of the selection process. If you require accommodation in order to apply for a job, please contact us at accommodationrequest yeti.com .

Requirements

Must-haves

What You ll Do
Work cross-functionally across engineering, product, sales, and various other teams in support of successful implementations.
Modernize core data infrastructure and data sets to support planned business growth.
Gather business and functional requirements and translate these requirements into robust, scalable, operable solutions with a flexible and adaptable data architecture.
Identify, design, and implement engineering process improvements through automating manual processes, optimizing data pipelines, re-designing services for greater scalability.
Collaborate with BI Engineers, Software Engineers, Data Scientists and other business stakeholders to deliver high quality data architecture and pipelines.
Provide strategy and tools necessary for data exploration, reporting and ability to move towards Artificial Intelligence (AI) and Machine Learning (ML) models.
Establish and maintain best practices, standards, and governance for data quality, security, privacy, and compliance across the analytics platform and services.
Develop and implement Enterprise Integration strategy, lead the implementation of a scalable API first integration platform.
Lead enterprise integrations capabilities covering all data movement across supply chain, merchandising, finance, store, ecommerce, HR, etc.
Hire and lead a team of data engineers and analytics professionals.
Develop and execute strategies for maintaining and enhancing our enterprise data solutions, including networks, servers, storage, and cloud services.
Build the frameworks required for optimal extraction, transformation, and loading of data from a wide variety of data sources using GCP technologies.
Build analytics tools that utilize the data pipeline to provide actionable insights and integrate insights with various consumer touchpoints.
Oversight of managed services contract for the run and maintain of the data warehouse, analytics platform and services, ensuring service level agreements and quality standards.
Collaborate with vendors and partners to optimize technology solutions.
Collaborate with cross-functional teams to ensure seamless equipment lifecycle processes.
Bachelor’s degree required
Greater than 15 years of experience in Technology roles, with extensive experience in data engineering and integrations, or equivalent combination of education and experience
Greater than 10 years of people management experience, managing both internal and external (contract) resources of varying seniority
Strong understanding of next gen data practices (e.g., MLOps, Data Ops, Data Science) and experience applying them in an enterprise organization.
Fluent in data technologies such as data governance tooling, data platform technologies, and enterprise/data architecture principles.
Analytical mindset for addressing complex challenges
Passion for building outstanding teams and creating an environment where individuals can do their best work

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aimachine learningapimlgcp

Platform: workday
Effort: long