Director Of Data Engineering

What you'll do:

• As a Director of Data Engineering, you will be instrumental in driving innovation, ensuring data quality, and fostering collaboration across teams to harness the power of data for informed decision-making
• Collaborate with the Business Intelligence team as well as Operators, Merchants, Marketers, Department heads, etc. to define use cases, solutions, cross-functional projects, and priorities
• Own end-to-end implementation for complex analytics solutions throughout the company, which could include reporting, simulations, custom tooling, and models
• Maintain a holistic vision of the organization, its data, and its customers enough to recognize and even anticipate their data needs
• Be the champion for data from a technical perspective across the entire organization
• Provide technical leadership in data architecture, ensuring best practices for data modeling, storage, and retrieval
• Maintain and improve the reporting infrastructure (Looker, Databricks and AWS Redshift) throughout the organization, maximizing the usability and adoption throughout the organization
• Design efficient data pipelines that can scale with the business
• Gather, transform, clean, and secure data from many sophisticated, state-of-the-art sources and destinations ensuring data quality, integrity and compliance with industry standards
• Drive the adoption of advanced analytics techniques and technologies to unlock insights from large datasets
• Mentor, lead and train other members of the data engineering team
• Stay current with emerging trends and technologies in the data engineering field, incorporating them into the organization's data strategy
• Respectfully and energetically express your thoughts and data philosophy to non-technical SMEs, backing up clear reasoning behind all tool & infrastructure decisions/proposals
• Establish and enforce data security and privacy protocols to safeguard sensitive information
• Drive the adoption of agile methodologies and DevOps practices to ensure efficient and high-quality data engineering processes

What you'll bring:

• BA/B.Sc. in Computer Science, Statistics, Math's or equivalent
• 8+ years of experience in data engineering or full-stack quantitative analytics/data science roles
• Proven track record of mentorship, leadership, and ownership within teams and organizations
• Proficiency in programming languages such as SQL and Python in an analytics context
• Experience with data pipelines, dimensional modeling, and dependency management
• Experience working with data SaaS and BI tooling (Fivetran, Looker, Databricks, etc.)
• Experience developing and managing a Looker instance
• Experience automating data integration using APIs
• Experience transforming open-ended objectives into well-defined requirements and delivering analytics solutions for multiple teams
• Deep knowledge of analytics technologies, modeling techniques, data warehousing concepts, cloud platforms (AWS preferred) and frameworks, and proven experience with data architecture
• Curiosity and creativity, with sound judgment and a high degree of both integrity and empathy
• Ability to create strategies and plans that define how information can be utilized to support an organization's overall business strategy, and how that information and data is organized, and governed inside an organization
• Experience with agile methodologies, DevOps practices, and CI/CD pipelines
• Communication and leadership experience, with experience initiating and driving projects
• Effective written and verbal communication of data-driven solutions across all levels of the organization
• Significant experience in consumer, retail or ecommerce organization