Engineering Manager - Python [DWH Data Tools]

Responsibilities

• We are looking for an experienced and driven Engineering Manager to manage our DWH Data Tools team. This team is responsible for managing and evolving our critical data ecosystem tools, including Superset, Jupyter Hub, and DataHub, while also developing new, in-house solutions - including internal BI and data-exploration tools - to fit specific business needs.
• This role merges technical leadership with comprehensive team management. The ideal candidate will possess strong leadership skills and technical expertise across the team's stack - Python, plus Node.js and Go - along with a proven track record managing engineering teams and data platforms. You will be pivotal in planning, optimizing development processes, and translating product ideas into robust technical solutions that solve real user pain points - often while navigating shifting priorities and evolving business needs.
• People Management: Lead, mentor, and manage a team of engineers. Take ownership of their performance, regular 1-on-1s, and continuous professional development
• Product Collaboration & Solution Brainstorming: Collaborate closely with product stakeholders to understand user pain points. Lead the brainstorming of technical solutions and translate product vision into actionable designs
• Planning & Execution: Drive planning activities for the team. Create and manage development plans, adeptly handling flexible deadlines and shifting business priorities
• Architecture & Development: Oversee the architecture, design, and implementation of data tools (Superset, Jupyter Hub, DataHub) and lead the development of custom solutions to meet new business requirements
• Stakeholder Communication: Manage communication with data engineers, analysts, and other stakeholders to ensure seamless data integration and tool usability
• Hiring, development, performance, and delivery management and strong skills in cross-functional collaboration and the ability to build partnerships
• Strong technical expertise in designing, deploying, and managing data tools (e.g., BI platforms, data notebooks, or data catalogs)
• Proven ability to manage flexible planning, balancing dynamic priorities and deadlines

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