Title: Director, Data Engineering
Location: Chicago, IL 

Position Overview
As Director of Data Engineering, you will play a crucial role in developing complex data structures and data pipelines. You will work on high-profile advanced data projects that drive the company’s decision-making and strategy. As a key member of the IT Leadership team, you will advance our data engineering capabilities and help the team’s data scientists to analyze data better and faster. Most data and analytics work support Zoro business verticals with similar business functions as identified below.

• Customer Service
• Products and Pricing
• eCommerce
• Marketing
• Finance

Reporting directly to the CIO this role will play a pivotal role in the effective execution of core and future business initiatives.

Job Responsibilities

• Lead all data engineering activities for Zoro
• Build a high performing organization
• Establish systems and processes for data-driven work
• Work closely with data engineers and data scientists to understand the business problems they are trying to solve and direct them to build the best-suited data structures for their analysis
• Build strong partnerships with peers across the organization to support data-related goals
• Continuously build on data engineering learnings and contribute input into best practices to make analytics more effective in future projects.
• Anticipate data modelers needs and proactively design intuitive data structures
• Direct and develop other employees to ensure best in class data assets
• Assess and communicate quality of analytical data
• Value data integrity by reconciling and documenting it at various stages
• Discover and explore new sources of data with curiosity and creativity
• Identify solutions to link new sources to internal data and provide the appropriate level of documentation of sources and technical solutions.
• Perform requirements planning, monitoring and end-to-end requirements management throughout the data asset development life-cycle
• Provide thought leadership and direction in the development and delivery of data-driven solutions
• Lead data remediation efforts

Desired Skills

• Strong problem solving and critical thinking skills
• Ability to attract, hire and retain top talent by fostering a culture of empowerment and curiosity
• Experience with development or selection of appropriate models that inform business decisions regarding customer behavior
• SQL skills required, with a specific focus on large data set manipulation for analytics
• Ability to communicate effectively to different target audiences
• Flexible and able to meet changing requirements and priorities
• Hands on experience looking into data issues leading to resolution or acceptance
• Ability to operate independently and manage tasks by engaging people across the team
• Exceptional teamwork skills required to play a key role in cross-functional teams
• Ability to collaborate and build trusting relationships
• Natural curiosity to understand the world around you and question as needed
• Comfortable handling ambiguous concepts and breaking down complex problems into manageable pieces
• Robust understanding and working with Business Intelligence requirements and reporting in an eCommerce context
• Demonstrated understanding of B2C and B2B behavior and predictive modeling differences and similarities

Required Education/Experience

• Undergraduate Degree in Computer Science, Engineering, Statistics, Mathematics, Data Analytics, or equivalent
• Masters or PhD in similar discipline a plus
• In-depth understanding of data warehousing concepts and design
• Demonstrated experience building data structures to support analytics/research/predictions in an eCommerce setting
• Proven record of people and leadership management
• Experience in R or Python and unstructured data
• Knowledge of specific ‘Big Data’ technologies such as RedShift and BigQuery
• Strong business judgment and ability to think through and solve complex problems
• Comfort with ambiguity and ability to get to the right answer at a reasonable level of precision (“80/20” rule)