Director of Data Platform Engineering (26-27)

Description

Director of Data Platform Engineering

This is a vacancy for the 26-27 school year with a target start date of July 1, 2026

Mission

The Director of Data Platform Engineering leads the team responsible for building, operating , and optimizing IDEA's data infrastructure. This leader ensures the data platform is reliable, scalable, secure, and performant-enabling Analytics Engineering, Data Science, Business Intelligence, and Research teams to deliver insights that improve student outcomes across IDEA Public Schools.

Reporting to the Managing Director of Data Platform & Engineering, this role translates architectural vision into operational reality through disciplined engineering execution, automation-first practices, and a relentless focus on platfor m reliability. This leader manages the platform engineering team through IDEA's critical transition from legacy ETL systems to a modern Snowflake-based data lakehouse , balancing the urgency of modernization with the stability requirements of production operations.

This role is central to achieving IDEA's goal of reducing data source onboarding from years to days through automated ingestion, robust orchestration, and comprehensive DataOps practices.

Supervisory Responsibilities:

Directly manages Data Platform Engineers - Build and maintain cloud data infrastructure, Snowflake environments, and ingestion pipelines

Location:

This is a full-time position based in Texas, with preference given to candidates who live in Austin, El Paso, Houston, Permian Basin (Midland/Odessa), Rio Grande Valley, San Antonio, and Tarrant County (Fort Worth), or who are willing to relocate.

Travel Expectations:

10% travel for team collaboration, critical implementations, and leadership meetings. May include occasional visits to IDEA campuses and headquarters.

What You'll Do - Accountabilities

Essential Duties:

• Build, mentor, and grow a high-performing platform engineering team of 4 direct reports with diverse skill sets (infrastructure, automation, legacy systems)
• Lead day-to-day build out and operation of IDEA's Snowflake-based data platform ensuring production-grade reliability, security, and performance
• Oversee Snowflake environment management including warehouse sizing, resource monitors, cost optimization, role-based access control, and performance tuning
• Ensure platform infrastructure meets defined SLAs for data freshness, pipeline reliability, and system availability
• Implement monitoring, alerting, and incident response processes that surface issues early and drive durable fixes
• Partner with IT Security and Data Governance to ensure platform meets enterprise standards for access controls, audit trails, and compliance
• Oversee implementation and operation of automated ELT pipelines from 20-30+ source systems (PowerSchool, assessment platforms, SIS systems, financial systems) into Snowflake

Additional Duties and Responsibilities:

• Ensure ingestion pipelines meet standards for reliability, data freshness, schema evolution handling, and error recovery
• Lead evaluation and operational management of ingestion tools (Fivetran, Airbyte) ensuring consistent implementation patterns
• Partner with Analytics Engineering to ensure Bronze layer (raw data landing) supports downstream transformation needs without creating coupling
• Drive "onboarding in days not years" goal through templated ingestion patterns, automated connector setup, and self-service enablement
• Monitor data pipeline health through observability dashboards and proactive alerting
• Partner with DataOps Engineer to embed CI/CD, automated testing, and deployment automation across all platform work
• Ensure infrastructure-as-code practices (Terraform) for all Snowflake resources, reducing manual configuration and enabling reproducibility
• Implement deployment standards including version control (Git), code review, automated testing, and rollback procedures
• Drive platform reliability through SLO/SLA definition, error budgets, and post-incident reviews that prevent recurrence
• Establish observability practices ensuring visibility into pipeline performance, data quality, costs, and system health
• Balance reliability work (automation, monitoring, technical debt) with delivery commitments (new data sources, platform features)
• Serve as primary technical partner to Manager of Analytics Engineering, ensuring platform capabilities support dbt development, testing, and data product delivery
• Work closely with Data Platform Architect to implement architectural standards faithfully while surfacing execution challenges and operational realities that should inform future design
• Collaborate with Director of Data Governance to ensure platform enforces data quality rules, access policies, and metadata standards
• Partner with Director of Business Intelligence and MD of Data Science & Analytics to understand platform requirements for dashboards and advanced analytics
• Interface with IT infrastr