Director, Data Engineering
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:
The ideal candidate is an experienced data engineering leader with a strong technical foundation, proven people management experience, and the ability to operate strategically while remaining hands-on. They should be comfortable leading complex initiatives, influencing stakeholders, and building high-performing engineering teams.
- 8+ years of experience in data engineering, software engineering, or related technical disciplines, including 4+ years managing engineers.
- Experience building and leading multidisciplinary data teams across areas such as data engineering, machine learning, analytics, or software engineering.
- Advanced proficiency in SQL and Python, with strong knowledge of data modeling, master data management, and data architecture principles.
- Hands-on experience with modern data platforms such as Snowflake, dbt, and orchestration tools including Airflow, Dagster, or Prefect.
- Proven ability to define and implement AI and LLM enablement strategies, including experience building with AI tooling.
- Experience operating at a Director level, including ownership of budgets, roadmaps, technical strategy, and executive communication.
- Strong leadership, mentoring, collaboration, and communication skills with the ability to explain complex technical concepts to non-technical stakeholders.
- Experience with AI agents, LLM-based systems, retrieval workflows, or tool-based AI orchestration is a plus.
- Familiarity with backend engineering, machine learning operations, data governance, privacy practices, and business systems integrations is advantageous.
Benefits:
- Competitive compensation package with a base salary range of $200,000 - $230,000 plus a 15% bonus opportunity.
- New hire stock grant.
- 100% employer-paid medical, dental, and vision insurance for employees and dependents.
- 401(k) plan with company contribution.
- Generous paid time off policy.
- Paid parental leave.
- Remote work flexibility within the United States or Canada.
- Opportunity to own and shape a high-impact data function with company-wide visibility.
- Ability to define the foundation for future AI, automation, and data-driven innovation.
- Collaborative environment with strong emphasis on growth, ownership, and technical excellence.
How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.