Manager of Data Engineering

Key Responsibilities

• Lead the design, development, and operation of scalable, production-grade data pipelines across e-commerce, CRM, ERP, order management, inventory, and marketing systems.
• Architect and evolve the enterprise data platform, including data lakes, data warehouses, semantic layers, and APIs for analytics and downstream consumption.
• Ensure data reliability, quality, lineage, observability, and performance across all pipelines and datasets.
• Drive adoption of modern data engineering tools and best practices, including orchestration, transformation, and CI/CD for data workflows.
• Enable E-Commerce Analytics by partnering with product, marketing, merchandising, and operations teams to define and deliver trusted datasets that support: Customer conversion and lifetime value analysis, Product and category performance insights, Personalization, loyalty, and experimentation use cases, Support near-real-time and real-time data flows to enable personalization engines, marketing tech, and A/B testing platforms, Implement self-service AI and analytics tools to replace manual, fragmented report requests.

Leadership & Cross-Functional Collaboration

• Manage, mentor, and grow a team of data engineers and data analysts, fostering a culture of technical excellence, accountability, and continuous improvement.
• Translate business requirements into scalable technical solutions, balancing short-term delivery with long-term platform health.
• Define and enforce data architecture standards, documentation, and governance practices.
• Influence data strategy and roadmap in alignment with broader digital and brand experience goals.

Governance, Security & Compliance

• Establish and maintain data governance, privacy, and access controls in line with GDPR, CCPA, and internal security standards.
• Partner with Security and Risk teams to support audits, data classification, and incident response related to data systems.
• Prepare for the future by establishing an internal AI strategy that raises the productivity of the entire company, extending the data platform to support externally-facing AI features.

Qualifications

• 5-8 years of experience in data engineering or analytics engineering, with 1-3 years in a leadership role.
• Proven experience building and operating large-scale data platforms in an e-commerce or digital business.
• Strong hands-on experience using modern data tools and frameworks.
• Experience with cloud data platforms and warehouses such as Snowflake, BigQuery, Redshift, Looker, Tableau, dbt.
• Demonstrated ability to deliver reliable, high-quality data products that support analytics, reporting, and machine learning.