Data Engineer Manager
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Job Description
Lead, design, and scale data solutions to support Journey Analytics initiatives, with a strong focus on code quality, reusability, and reliable data platforms. This role is responsible for setting the technical direction, overseeing the evolution of data architectures, and leading a team of data engineers to deliver high-quality, performant datasets for analytics and reporting use cases.
The ideal candidate combines strong hands-on data engineering expertise with people leadership experience, and has a proven track record of driving scalable solutions in cross-functional environments.
Responsibilities
• Lead and mentor a team of data engineers while actively contributing to development efforts and setting best practices in coding, architecture, and data engineering standards.
• Define and drive the technical strategy for Journey Analytics data platforms, while remaining hands-on in the design and implementation of scalable solutions.
• Actively contribute to the maintenance, optimization, and automation of code repositories in GitHub, ensuring high-quality and consistent development practices.
• Participate directly in refactoring legacy codebases to improve maintainability, scalability, and reusability across multiple use cases.
• Design and build modular, reusable data components to support multiple journeys and reduce duplication.
• Develop and manage automated data pipelines in Databricks, ensuring reliability and scalability for downstream consumption.
• Design and implement scalable data models to support current and future analytics use cases.
• Ensure data quality, governance, performance, and reliability across all data pipelines and datasets through both oversight and direct contribution.
• Collaborate closely with analytics, product, and engineering stakeholders to align data solutions with business needs and priorities.
• Proactively identify risks, bottlenecks, and improvement opportunities, and take a hands-on role in driving mitigation strategies.
• Promote continuous improvement of data processes, documentation, and engineering practices through both leadership and execution.
Requirements
Function: Marketing
Experience Level: Mid-Senior Level