Director, Data Engineering - jobgether

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Director, Data Engineering based in the United States.

This role offers the opportunity to shape and lead a critical data organization within a fast-growing technology environment. You will define the long-term data strategy, architecture, and engineering practices that enable smarter decisions, automation, and AI-powered innovation. As a player-coach leader, you will balance hands-on technical execution with team development, mentoring, and organizational growth. You will build scalable data foundations, establish trusted systems, and guide a multidisciplinary team across data engineering, machine learning, and analytics. The role provides significant ownership, executive visibility, and the ability to influence how data is used across the entire organization. The ideal candidate is a technical leader who thrives in ambiguity, enjoys solving complex challenges, and is passionate about building high-impact teams and platforms.

Accountabilities:

The Director, Data Engineering will own the vision, strategy, and execution of the organization’s data platform while leading a growing team of engineers and analytics professionals. This role requires a combination of deep technical expertise, strategic thinking, and leadership capabilities to create reliable data systems that support business intelligence, automation, and emerging AI initiatives.

• Define and execute the long-term data strategy and architecture, ensuring scalable, reliable, and trusted data foundations.
• Design, build, maintain, and optimize high-impact data pipelines connecting business systems, internal platforms, and data warehouses.
• Establish engineering standards for pipeline development, data modeling, governance, quality, and operational excellence.
• Act as a hands-on technical leader by contributing directly to complex projects, resolving technical challenges, and guiding engineering decisions.
• Build, structure, and lead a multidisciplinary Data organization spanning Data Engineering, Machine Learning Engineering, and Analytics.
• Own team growth initiatives, including hiring plans, organizational design, budget planning, and talent development.
• Partner with executive and cross-functional leaders to translate business goals into data strategies, platform investments, and technical roadmaps.
• Evaluate existing integrations, automation processes, and data workflows to identify opportunities for improvement and modernization.
• Champion AI and automation initiatives by ensuring emerging technologies are supported by reliable, scalable data infrastructure.

Requirements: