Senior Agentic Data Engineer (IC3)

At ClassLink, we believe learning should be accessible, engaging, and empowering for every student, every educator, everywhere. That’s why we build secure, intuitive tools that empower more than 26 million students and educators worldwide. From simplifying access with single sign-on, to advancing equity with usage analytics, to automating secure rostering, our platform helps schools focus on what matters most: teaching and learning.

We’re not just building tools, we’re building what’s next in education. By removing barriers and enabling data-driven decisions, our solutions help educators lead with confidence and students thrive in and out of the classroom every day.

Our team is driven by purpose and grounded in three core values:

• Strive to Grow - always learning, improving, and innovating.
• Deliver Worthwhile Experiences - for our users, our partners, and each other.
• Contribute with Heart - putting people first in everything we do.

These values shape how we work, innovate, and support the communities we serve. If you’re ready to do work that makes a real difference, and grow alongside a team that values collaboration, support, and continuous improvement. ClassLink is the place for you.

ClassLink is seeking a Senior Agentic Data Engineer (IC3) who will lead the design and evolution of scalable data platforms, cloud-native services, and AI-enabled data capabilities that support ClassLink’s products, analytics, and technology strategy. This role designs enterprise data architectures, establishes engineering best practices, and delivers secure, reliable, high-performing data solutions, integrations, and reusable frameworks. Working across Product, Engineering, Security, Infrastructure, and Analytics, the Senior Data Engineer guides technical decisions, conducts architecture and code reviews, and mentors other engineers. Success requires deep expertise in data engineering, cloud-native platforms, distributed systems, data governance, and technical leadership.

Responsibilities:

AI-Enabled Data Engineering & Technical Excellence

• Lead the development of complex data platforms, cloud-native data services, enterprise integrations, and scalable data pipelines across multiple products and systems.
• Establish engineering best practices for AI-assisted development, data engineering, data quality, observability, testing, security, and software reliability.
• Evaluate emerging data technologies, AI-enabled engineering capabilities, and cloud services while guiding technical adoption across engineering teams.
• Champion AI-assisted engineering tools, intelligent automation, and modern data engineering practices that improve developer productivity, data quality, and engineering effectiveness.

Accountability & Results

• Design scalable data architectures that balance maintainability, security, performance, scalability, reliability, and business objectives.
• Lead technical implementation for complex data engineering initiatives while guiding engineering teams through architectural decisions and implementation tradeoffs.
• Design and optimize multi-tenant data platforms, REST APIs, ETL/ELT pipelines, event-driven data integrations, data warehouse solutions, and cloud-native data services.
• Ensure data engineering solutions meet established standards for data quality, governance, testing, operational readiness, security, and compliance.

Operational Excellence & Continuous Improvement

• Drive improvements in data engineering automation, developer productivity, platform reliability, data quality, and delivery efficiency.
• Develop reusable frameworks, data engineering standards, technical documentation, reference architectures, and tooling that benefit multiple engineering teams.
• Identify systemic data engineering challenges and implement long-term improvements that strengthen platform scalability, operational resilience, and engineering effectiveness.
• Optimize AWS-based data platforms through automation, monitoring, observability, cost optimization, and performance tuning.

Collaboration & Communication

• Partner with Product Management, Software Engineering, Architecture, Infrastructure, Quality Engineering, DevEx, and other technical leaders to align data solutions with product strategy and organizational priorities.
• Lead technical discussions, architecture reviews, cross-team engineering initiatives, and enterprise data integration efforts.
• Mentor Data Engineers through technical coaching, design reviews, code reviews, and knowledge sharing while promoting engineering excellence.
• Influence engineering decisions by promoting modern data architecture, cloud-native engineering practices, data governance, and operational excellence.

This role is remote with quarterly in-person strategy meetings.

NOTE: This job description is not intended to be all-inclusive. Employees may be asked to perform other related duties as negotiated to meet the ongoing needs of the organization.