Director, Data Products & Engineering

Accountabilities:

• Own the end-to-end lifecycle of data products, from ideation and design through development, delivery, and continuous optimization.

• Establish and mature product-oriented data practices, including backlog management, prioritization frameworks, and iterative delivery cycles.

• Lead the design and delivery of scalable data products and platform capabilities on modern cloud data infrastructure (e.g., Databricks ecosystem).

• Guide data modeling, semantic layer development, and implementation of best practices for reusable and trusted data assets.

• Enable and support a data mesh approach by empowering domain teams to own and manage their data products effectively.

• Lead, mentor, and develop a team of data engineers, fostering strong execution, accountability, and technical excellence.

• Partner closely with cross-functional stakeholders to translate business needs into high-value data solutions.

• Drive adoption of modern engineering practices, including AI-assisted development and automation where applicable.

• Manage multiple concurrent initiatives while communicating progress, risks, and dependencies to stakeholders.

• Ensure data products deliver measurable impact, including improved accessibility, adoption, and time-to-insight.

Requirements:

• 8–12 years of experience in data engineering, data products, or software engineering roles.

• 3–5 years of experience leading technical teams and delivering complex data initiatives.

• Strong experience applying a product mindset to data, including prioritization, roadmap planning, and user-focused delivery.

• Experience with modern data platforms, data modeling, and scalable data architecture principles.

• Familiarity with data mesh or domain-oriented data ownership models is strongly preferred.

• Proven ability to lead and scale high-performing engineering teams.

• Experience collaborating with business stakeholders to translate requirements into data-driven solutions.

• Strong communication skills with the ability to bridge technical and non-technical audiences.

• Bachelor’s degree or equivalent practical experience in a related field.

• Experience with Databricks or similar modern data ecosystem tools is a plus.

• Exposure to AI-assisted development practices is highly valued.

Benefits:

• Competitive and mission-driven work environment within a growing education technology organization.

• Opportunity to lead and shape enterprise-wide data product strategy and architecture.

• Work with modern cloud-based data platforms and emerging AI-enabled engineering practices.

• Collaborative, cross-functional culture focused on impact, innovation, and scalability.

• Leadership role with direct influence on data strategy and organizational decision-making.

• Opportunity to build and scale a high-performing data engineering team.

• Commitment to diversity, equity, and inclusion across the organization.

• Remote-friendly or flexible work arrangements depending on organizational policy.

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!
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