Senior Engineer, Analytics

The Role

As a Senior Engineer at Apptegy, you’ll play a key role in shaping the architecture, performance, and scalability of our platform. This role is a unique hybrid that bridges traditional application development with data engineering. You will be responsible for building and scaling our analytics and data platform.

You will own the delivery of reliable, high-performing software and data systems, working primarily with our Ruby on Rails backend services, while building efficient data pipelines to transfer and transform data from PostgreSQL to Snowflake. This role is ideal for an engineer who thrives in a fast-paced environment and enjoys building systems from the ground up that provide meaningful, real-time insights to educators and students.

What You’ll Do

Technical Execution & Strategy

• System Architecture: Take responsibility for designing system architecture and scalable data models, ensuring scalability, security, and performance across the entire platform.
• Backend Development: Implement event-capture frameworks within our Ruby on Rails services (e.g., shared gems and event schemas).
• Pipeline Engineering: Design and build event-driven data pipelines specifically engineered for in-product analytics, ensuring data is cleaned, modeled, and optimized to power user-facing insights and reporting features.
• Process Optimization: Decompose large, complex tasks into manageable units of work to ensure efficient execution.
• Problem Solving: Proactively anticipate potential technical challenges before they arise and approach challenges with a solutions-focused mindset.
• Strategic Alignment: Collaborate with product managers and engineers to align technical and data efforts with business goals and long-term strategy.

Leadership & Collaboration

• Mentorship: Actively share knowledge of software and data engineering best practices and ensure quality standards are followed throughout the development cycle.
• Data Quality: Lead the development of unit and integration tests with quality gates to ensure both code reliability and the integrity of data served within the product.
• Collaboration: Work effectively within teams, valuing diverse perspectives and improving cross-team collaboration to manage timelines and resources effectively.
• Communication: Proactively share ideas, progress, and questions with stakeholders to ensure alignment, while clearly explaining complex technical decisions and their implications.

What You’ll Bring

Experience & Technical Skills

• Experience: 5+ years of professional software development experience, with a focus on backend services and engineering data for analytics.
• Backend Proficiency: Strong experience building backend systems (Ruby on Rails, Python, or similar).
• Data Engineering: Deep experience with SQL, data modeling, and building scalable, reliable event-driven data pipelines using a medallion architecture (bronze/silver/gold layers).
• System Design: Experience designing and building scalable, high-performance systems.
• Process: Mastery with Scrum processes and a track record of effectively prioritizing tasks to meet deadlines and project goals.

Behavioral Competencies

• Ownership: Demonstrates accountability by taking full responsibility for systems and proactively addressing obstacles.
• Adaptability & Curiosity: Adjusts smoothly to new tools and evolving requirements while seeking to learn new technologies.
• Analytical Problem Solving: Approaches complex data and software needs with a solutions-focused mindset and possesses excellent debugging skills.

What Makes You Stand Out

• Cloud Platforms: Experience with AWS; relevant certifications (AWS Certified Solutions Architect Associate, AWS Certified Data Engineer) are a plus
• Database Technologies: Experience with database technologies (e.g., RDS/Aurora PostgreSQL, Snowflake). Experience replicating data via Change Data Capture (CDC) from PostgreSQL to Snowflake.
• Semantic Layers: Familiarity with Semantic reporting layers and headless BI frameworks (e.g., Cube.dev) to support consistent, scalable in-product analytics.
• DevOps & Infrastructure: Knowledge of DevOps practices and tools (e.g., Terraform, CI/CD, Docker, Kubernetes).
• AI-Enhanced Development & Testing: Proficiency in leveraging AI coding assistants (e.g., Cursor, Claude Code) to accelerate code generation, refactoring, and the development of robust unit and integration tests across the full stack (Vue.js, Ruby on Rails).
• Industry Experience: Experience in the education technology sector.