Director of Data & Analytics Engineering

A pioneer in K–12 education since 2000, Amplify is leading the way in next-generation curriculum and assessment. Our core and supplemental programs in ELA, math, and science engage all students in rigorous learning and inspire them to think deeply, creatively, and for themselves. Our formative assessment products help teachers identify the targeted instruction students need to build a strong foundation in early reading and math. All of our programs provide educators with powerful tools that help them understand and respond to the needs of every student. Today, Amplify serves more than 15 million students in all 50 states. For more information, visit amplify.com.

We are seeking a strategic and hands-on Director of Data & Analytics Engineering to lead our data engineering and analytics engineering functions. This leader will oversee the development of scalable data platforms, pipelines, and models that empower teams, applications, and agents across Amplify to make data-informed decisions and tell compelling stories with data.

In this role, you will partner closely with data science, AI, product, and engineering teams to deliver reliable, high-quality data solutions while building and developing a high-performing team of managers and engineers.

Essential Responsibilities:

This is a key leadership role responsible for developing and supporting engineering managers within the data department, overseeing both the data platform and analytics engineering functions.

• Leadership: Own and drive technical vision, architectural strategy, and cross-functional alignment across data and analytics engineering, while developing and empowering engineering managers to build, grow, and retain high-performing teams.

• Technical Leadership & Guidance: Guide and oversee architectural decisions to innovative architectures and tech stack decisions while fostering strong technical practices across data modeling, ingestion, ELT pipelines, MLOps, and platform operations.

• Strategy: Develop and implement data engineering and analytics engineering strategy in collaboration with the VP of Data and peer directors.

• People Management: Provide leadership, career development, coaching, mentoring, and building a strong leadership bench within the department

• Delivery: Be accountable for the successful delivery of annual OKRs and ensuring consistent execution against roadmap commitments across teams, leveraging best practices in estimation, requirements analysis, and balancing trade-offs.

• Communication and Collaboration: Work closely with business, product, data science, and engineering teams to ensure the data department develops tools that solve the most critical analytics challenges.

• Vendor & Cost Management: Evaluate build vs. buy decisions for tooling, manage vendor relationships, and optimize cloud infrastructure costs.

• Agentic Tooling: Champion the adoption and responsible use of agentic coding and analytics tools (e.g. Claude Code, Snowflake Cortex), establishing best practices for AI-assisted development and AI-augmented analytics workflows.

Required Qualifications:

• Bachelor’s degree in a relevant field (e.g. computer science, data science, engineering, mathematics) or equivalent experience

• 10+ years of experience in data engineering, analytics engineering, or related fields, including hands-on experience with modern data stack technologies (e.g., dbt, Snowflake, SQL, Python, Terraform)

• 5+ years of people management experience, including 3+ years managing managers.

• Proven ability to develop multi-year strategy and facilitate goal-setting processes (e.g. annual OKRs, product roadmaps) across multiple teams

• Experience with ETL/ELT pipeline design, data modeling, data platform architecture, and BI tools such as Looker and Tableau

• Experience with data observability and reliability tools (e.g. Monte Carlo, dbt tests, Great Expectations) to proactively monitor pipeline health and data quality.

• Familiarity with agentic coding tools (e.g. Claude Code, Snowflake Cortex), and AI-assisted development workflows, and a demonstrated ability to drive adoption of emerging technologies

• Excellent communication and interpersonal skills, especially with non-technical partners

Preferred Qualifications:

• Experience with metadata management tools such as Atlan

• Understanding of data modeling paradigms within a lakehouse environment and the judgment to apply the right architecture for the problem, from dimensional modeling (Kimball) and