Manager, Data Engineering - United States

Zenni Optical is a leader in the online eyewear industry, dedicated to making eyewear affordable and accessible. The Manager, Data Engineering will oversee a team and bridge the gap between data architecture and marketing initiatives, translating data into actionable insights to drive business growth.

Responsibilities:

• Champion data literacy: Provide ongoing training and support to the Engagement Marketing team, ensuring complex data concepts are seamlessly communicated and understood
• Drive cross-functional alignment: Act as the strategic bridge between the Data and Engagement Marketing teams, streamlining communication to boost operational efficiency and collaboration
• Power marketing platforms: Integrate enriched, highly trusted data with key business platforms (e.g.,Google, Tik Tok, Meta) to optimize ad delivery and AI performance
• Ensure data integrity: Own the lifecycle of data feeds, encompassing validation, monitoring, testing, and proactive alerting, to guarantee uncompromising data quality and reliability
• Define success metrics: Partner with functional teams to establish a shared, accurate understanding of the core metrics that drive organizational performance
• Shape the data roadmap: Lead the strategic planning for the data team, ensuring technical initiatives directly align with Zenni’s overarching growth objectives
• Innovate continuously: Stay at the forefront of modern data engineering technologies and industry trends to evolve our strategy and keep our technical capabilities competitive

Requirements:

• Bachelor's degree in Computer Science, Machine Learning, Engineering, or a related technical discipline
• 8+ years of dedicated experience in the data area, coupled with at least 3 years navigating the fast-paced e-commerce landscape
• Deep business domain knowledge across key marketing functions, including but not limited to Performance Marketing, Lifecycle, and Brand Marketing
• Hands-on experience implementing marketing measurement methodologies, including Last-Touch, MTA, incrementality testing, MMM, and CVR measurement frameworks
• Extensive experience designing data architecture, performing complex data modeling, and building scalable ETL/ELT pipelines for centralized data warehouses
• Advanced fluency in SQL and Python, with the ability to dive deeply into a modern tech stack as a hands-on contributor
• Demonstrated success leading projects from start to finish, spanning requirement gathering, cross-functional stakeholder communication, architecture design, implementation, and QA
• Proactive leadership and cross-functional communication skills, with a proven ability to drive business impact
• Hands-on expertise working within Databricks environments
• Proven track record of guiding and mentoring high-velocity data teams in a fast-paced setting
• Demonstrated success managing complex data integrations, advanced reporting, and platform optimization across diverse marketing channels
• An enthusiastic, proactive approach to tackling new technical challenges and driving continuous improvement