Join the Data Solutions Engineering as a Director of Datawarehouse & Analytics and be part of Staples exciting journey to redefine customer experience and deliver new brand, products and services to our customers. We are on a digital transformation journey in which Staples will continue to leverage its data in new and exciting ways including Artificial Intelligence and Machine Learning (ML/AI). We are seeking an accomplished and forward-thinking director with a specialized focus on ML/AI, Data Architecture, Analytics and Datawarehouse. You'll play a pivotal role in building and defining state-of-the-art analytical models and data solutions architecture for the growing data needs of our North American Delivery (NAD) organization.

As the senior leader of a team of highly skilled data engineers and contractors with varied experience levels, you'll guide the development of data structures and pipelines that organize, collect, and standardize data to generate insights and address reporting needs. Your team will be responsible for writing ELT (Extract / Load / Transform) processes, designing data ingestion/extraction frameworks & systems, and developing tools for real-time and batch analytics processing. You'll also oversee the integration of data from a variety of sources, ensuring that it adheres to data quality and accessibility standards and help lead our ML and AI journey forward. In this role, you'll be responsible for planning and reviewing the work of your associates through code reviews and participating in scrum events and other Agile ceremonies. This is a fantastic opportunity to make a real impact on the future of Staples and drive innovation in our retail ecommerce enterprise.

What you’ll be doing:

• Ensuring that project/department milestones/goals are met and adhering to approved budgets.
• Develop strong relationships with business stakeholders and product owners.
• Define and deploy data architecture and enable top-down governance models.
• Develop and communicate a roadmap for the organization's analytics, machine learning, and AI capabilities aligned with business goals and market trends.
• Oversee design and the creation of data architecture (models) and repositories.
• Develop data products from proof of concept to scalable solutions based on business priorities and impact, using modern tools and technologies on cloud.
• Champion technical design whiteboarding sessions to enable open discussion with architects, engineers & technologists.
• Enable data driven decision making: Advance access to information for decision making into wide populations of business users, by enabling them to access data & analytics via easy combinations of elements.
• Increase adoption of data & analytics (D&A) via self-service and data catalog.
• Managing the flow of data from internal and external sources by leveraging both distributed and local data structures.
• Support mission critical applications and near real time data needs in the data platform.
• Participate in design and code reviews.
• Work with cybersecurity teams and infrastructure teams to secure and protect valuable data from inappropriate access or data loss.
• Work with disaster recovery planning and execution with other team members.
• Determine risk potential for various configurations and options for data administration and able to communicate issues to managers and team as required.

What you bring to the table (Soft Skills):

• You will work hand in hand with business stakeholders, product owners, scrum masters to deliver quality work and will be able to exercise independent judgment.
• Work collaboratively with fellow directors, project managers, technical data managers, data architects, data scientists as well as business partners.
• Work as part of an engineering team from concept to operations, providing deep technical subject matter expertise for successful deployment.
• Accountable for the management of several segments in the enterprise data space.
• Interact with direct reports and peers in management / customers / vendors to share information and improve cross-departmental processes.
• Be capable of leading a large and complex team in Data Solutions Engineering.
• Ensure the ongoing training and development of direct and indirect reports.

Basic Qualifications:

• Bachelor’s Degree or equivalent in Computer Sciences, Data Analytics, Management Information Systems, or related quantitative field in Data Engineering
• Demonstrated experience managing and migrating data warehousing capabilities to the Snowflake platform or similar platforms.
• A history of developing managing large complex budgets and drafting compelling business cases.
• Proven experience (8+ years) in leading analytics, machine learning, and AI initiatives, with a track record of successful project delivery.
• Strong understanding of data management, statistical analysis, machine learning algorithms, and AI technologies.
• Previous hands-on experience with languages like Python, PySpark, SQL, UNIX/Linux scripting to access, extract, manipulate and summarize data.
• Demonstrated success leading teams executing enterprise data engineering, database optimization, data processing, data cleansing and automation.
• Experience working with: Airflow, Kubernetes, Cloud infrastructure (e.g., Azure, GCP), CI/CD (e.g., Azure DevOps, Git actions, Jenkins, or CircleCI) and automated testing.
• Familiarity with a broad base of analytical methods like data modeling, variable based transformation & summarization, and algorithmic development.
• Excellent leadership and communication skills, with the ability to influence and collaborate with stakeholders at all levels.
• Experience in enabling a data marketplace solution, increasing reach of data products, and simplifying understanding and access for all consumers.

Preferred Qualifications:

• Masters degree in Computer Science, Business Administration or Data Science
• Experience in SnowSQL, GCP - BigQuery, Cloud SQL, DataFlow, Pub/Sub, Cloud Functions etc.
• Experience in developing User Defined Functions (UDF) in python, SQL, etc.