DataKind is looking for a Director, Engineering!

DataKind is seeking a Director, Engineer to lead the technical strategy and execution for our education software products at DataKind. This is an exceptional opportunity for a technical leader who enjoys hands-on engineering work while providing technical leadership. The ideal candidate will excel in ambiguous environments, creating structure and clarity while directly contributing to code and solving complex technical challenges.

Location

Remote position available anywhere in the U.S. with working hours primarily between 8am-6pm Eastern Time.

Salary Range

The salary range is $150,000 - $170,000.

Actual salary within this range will be based on the candidate’s experience and internal salary equity scan of active employee(s) with similar role and experience. 

About the Opportunity

Reporting to the Vice President, Technology, this role will serve as the primary technical contributor and architect for our two major education products, providing hands-on engineering leadership and strategic technical direction. The role will also oversee a team of data scientists and software engineers across our two major education products, providing technical leadership and strategic direction. 

In this role, you'll be deeply involved in the day-to-day technical work while establishing essential processes and infrastructure. Working closely with our Education Programs, Customer Success, and Data Security/Compliance teams, you'll ensure our software solutions meet customer and funder needs through both direct technical contribution and oversight.

Core Responsibilities:

The Director, Engineer will be responsible for the following, in addition to any other project assigned by the Vice President, Technology:

Hands-On Technical Development 

• Architect and build scalable technical solutions for our education products from the ground up
• Write production code and lead critical technical implementations across the full stack
• Design and implement core features, APIs, and data processing pipelines
• Debug and optimize system performance and resolve complex technical challenges
• Conduct code reviews and establish technical standards through example and direct contribution

Technical Infrastructure Design

• Establish scalable technical architecture and infrastructure to support the development and scale of our education products
• Design and implement standardized development processes, coding standards, and quality assurance practices
• Oversee the full software development lifecycle across multiple education products simultaneously
• Balance feature development with technical debt management and platform stability
• Implement metrics and analytics frameworks to measure product success and inform development priorities

Team Leadership & Collaboration

• Directly manage and mentor data scientists and software engineers for our education products

• Partner with Head of Education Programs and Director, Product Management  to translate educational needs into technical requirements and solutions
• Work closely with Customer Success to incorporate user feedback into technical planning
• Collaborate with Data Security and Compliance teams to ensure adherence to education-specific regulations

Resource Allocation and Growth Planning

• Develop realistic technical roadmaps that align with organizational resources and mission
• Establish resource allocation frameworks across products to maximize overall impact
• Align technical planning and resource allocation with grant commitments and milestone requirements

Qualifications

Required

• Alignment and enthusiasm for DataKind’s mission and values 
• 8+ years of hands-on software engineering or data science experience with 2-3 years in technical leadership roles 
• Passion for educational mission and commitment to social impact
• Strong full-stack development skills with experience in modern web technologies, databases, and cloud platforms
• Experience with data science workflows, including model development, deployment, and evaluation
• Strong understanding of data science applications in software products and ability to evaluate data science work
• Proven track record of building and shipping software products in resource-constrained environments
• Experience implementing agile methodologies suited to sma