Managing Director of Data Platform and Engineering (26-27)

IDEA Public Schools • Weslaco, TX

4d • $131,000 - $158,500 • Onsite

About The Position

Managing Director of Data Platform and Engineering This is a vacancy for the 26-27 school year with a target start date of July 1, 2026 Mission: The Managing Director of Data Platform & Engineering leads IDEA’s transformation to a modern, cloud-native data platform that enables rapid insights and self-service analytics across all states and departments. This leader is accountable for the successful delivery and operation of a scalable Snowflake-based data lakehouse , reducing data onboarding from years to days while maintaining operational excellence throughout the transition. This role is ideal for a visionary technologist who can balance strategic platform leadership with hands-on organizational leadership, driving IDEA toward a nimble data-driven culture that serves students, staff, and stakeholders. The MD of Data Platform & Engineering will sit on the leadership team and report directly to the Vice President of Enterprise Data & Strategy. Supervisory Responsibilities: Directly manages: Data Platform Architect Director of Data Platform Engineering Manager of Analytics Engineering DataOps Engineer 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: 15% travel to team meetings, leadership gatherings, regional offices, and occasional vendor/partner locations during critical implementation phases. What You’ll Do – Accountabilities Essential Duties:

Requirements

• Make Strategic Decisions: This team member uses data and trends to drive decisions that impact multiple teams, while anticipating risks and planning contingencies for key initiatives. They apply strategic frameworks to clarify challenges and guide coherent action, and they actively support others in strengthening their strategic thinking and decision-making capabilities.
• Manage Work and Teams: This team member designs scalable systems that anticipate future organizational needs, driving sustainable impact through cross-functional collaboration and strategic problem-solving. They foster a culture of ownership and accountability, lead change with clarity and purpose, and balance hands-on leadership with empowering others to build capacity and achieve long-term success.
• Grow Self and Others: This team member identifies development needs across multiple groups and integrates them into broader strategic plans. They create structures that support ongoing growth, engage in succession planning, and continuously refine development strategies based on outcomes and data. Through this work, they foster a culture where continuous learning is a core part of daily work and leadership.
• Build a Culture of Trust : This team member builds trust and drives positive engagement across multiple groups, as reflected in strong feedback and survey results. They proactively address concerns, model transparency and authenticity, and foster collaboration through open, honest communication and shared ownership.
• Communicate Deliberately: This team member communicates a clear and compelling vision that aligns team efforts with organizational goals. They proactively identify and address communication gaps across workstreams, implementing solutions to enhance coordination, while anticipating and resolving stakeholder concerns before they surface.
• Cloud Data Platform Architecture: Deep expertise in Snowflake architecture, performance optimization, cost management, and security models Experience with modern table formats (Iceberg, Delta Lake) and understanding of lakehouse architecture patterns Knowledge of cloud infrastructure (AWS/Azure/GCP) including networking, IAM, and service integration Understanding of data warehouse modeling techniques (Kimball, Data Vault, wide tables) and when to apply each
• Modern Data Stack & Tools: Hands-on experience with automated ingestion tools ( Fivetran , Airbyte , or similar) and ability to evaluate connector reliability Proficiency in dbt (data build tool) for transformation including testing, documentation, and package development Familiarity with orchestration platforms ( Dagster , Prefect, Airflow) for workflow management Experience with data quality frameworks (Great Expectations, dbt tests, Monte Carlo) and observability tools Knowledge of data cataloging and governance platforms (Atlan, Collibra, Alation)
• DataOps & Software Engineering Practices: Strong foundation in Git workflows, CI/CD pipelines, and infrastructure-as-code (Terraform) Experience implementing automated testing, deployment strategies, and rollback procedures for data pipelines Understanding of monitoring, alerting, and incident management for data platform operations Proficiency in Python and SQL for pipeline development and troubleshooting
• Data Architecture Patterns: Expertise in medallion architecture (Bronze/Silver/Gold layers) and understanding of decoupling strategies Experience with data mesh principles for domain-oriented, decentralized data ownership at scale Knowledge of semantic layers, metrics stores, and approaches to consistent business definitions Understanding of streaming architectures and event-driven patterns (Kafka, Event Hubs) for real-time use cases
• Visionary yet pragmatic: Can articulate ambitious 5-year vision while delivering incremental value quarterly
• Change management: Experience leading large-scale technical transformations with legacy system constraints
• Vendor/partner management: Skilled at evaluating, negotiating with, and managing implementation partners and technology vendors
• Influential communication: Can secure executive buy-in and funding for platform investments through compelling ROI narratives
• Bias toward action: Comfortable making decisions with incomplete information and course-correcting rapidly
• Talent magnet: Known for attracting, developing, and retaining top data engineering talent
• Education: Bachelor's degree in Computer Science , Data Engineering, Information Systems, or related technical field
• Experience: Minimum 10 years in data engineering, platform engineering, or data architecture roles with at least 5 years in leadership positions managing technical teams
• Cloud expertise: Demonstrated success implementing cloud data platforms (Snowflake, Databricks, or similar) in production environments
• Modern data stack: Hands-on experience with at least 3 modern data tools ( dbt , Fivetran / Airbyte , Great Expectations, etc.)
• Scale: Experience managing data platforms supporting 20+ data sources and hundreds of users across multiple business units or regions
• Team building: Proven track record recruiting, mentoring, and developing data engineering teams from 5-15+ members

Nice To Haves

• Advanced degree: Master's degree in related field or MBA with technical focus
• K-12 or education sector: Experience with student information systems (PowerSchool, Focus), assessment platforms, and education data standards
• Multi-state/multi-region: Experience building data platforms for geographically distributed organizations with federated operations
• Certifications: Snowflake certifications ( SnowPro Core/Advanced), dbt Analytics Engineering certification, or cloud platform certifications (AWS/Azure/GCP)
• Data mesh implementation: Direct experience implementing data mesh principles in production environments
• Startup/scale-up experience: Track record building data platforms in high-growth environments with rapid iteration
• Public speaking/writing: Conference presentations, blog posts, or open-source contributions demonstrating thought leadership

Responsibilities

• Define and execute a 3-5 year data platform strategy aligned with IDEA's multi-state presence and educational mission
• Drive the transition from legacy on-premises infrastructure to modern cloud data lakehouse architecture on Snowflake
• Establish architectural principles including medallion architecture (Bronze/Silver/Gold), data mesh for state autonomy, and ELT-first patterns
• Champion automation, self-service analytics, and DataOps practices to significantly reduce data onboarding
• Serve as technical thought leader, staying ahead of trends in cloud data platforms, modern data stack tools, and K-12 analytics engineering
• Work in close partnership with the other members of the Enterprise Data & Strategy leadership team
• Makes final decisions on all platform architecture based on recommendations from the Data Platform Architect. Accountable for both architectural outcomes and successful delivery of the platform
• Design and deliver a Snowflake-based data lakehouse architecture that balances performance, cost-efficiency, and strategic flexibility.
• Make informed technical decisions about table formats, transformation patterns, and tool selection based on IDEA's multi-state operations, growth trajectory, and vendor risk tolerance.
• Partner with the Data Platform Architect for deep technical analysis and recommendations, while maintaining final accountability for architectural decisions and their successful implementation.
• Ensure automated ingestion frameworks are implemented using tools like Fivetran or Airbyte to support extensive data sources with minimal manual coding
• Ensure a modern transformation layer using dbt Cloud is implemented with version control, automated testing, and modular design patterns
• Ensure implementation of a comprehensive data quality framework (e.g., Great Expectations, Monte Carlo) with automated validation and anomaly detection
• Ensure deployment of a data catalog and semantic layer in partnership with Business Intelligence and Data Governance, enabling consistent metrics and self-service discovery.
• Define and enforce data governance standards including lineage tracking, security controls, and compliance requirements
• Build, mentor, and grow a high-performing team
• Foster a culture of innovation, continuous improvement, and technical excellence with emphasis on automation and best practices
• Establish clear roles, responsibilities, and career development paths aligned with modern data engineering competencies
• Create operating mechanisms including sprint planning, code reviews, incident response, and knowledge sharing
• Balance maintenance of current production systems with aggressive modernization timelines
• Drive team upskilling in cloud-native technologies, dbt , DataOps practices, and modern data tools
• Sets and resolves DataOps prioritization across Platform Engineering and Analytics Engineering to balance delivery speed, reliability, and automation maturity.
• Partner with Managing Director of Data Science & Analytics, Director of Research and Evaluation, and Director of Business Intelligence to ensure platform serves all analytical needs
• Collaborate with business and academic leaders to understand domain-specific requirements and enable state autonomy through data mesh principles
• Serve as trusted technical advisor to senior leadership, translating complex architecture into business value and ROI
• Build relationships with IT infrastructure, security, and compliance teams to ensure platform meets enterprise standards
• Manage vendor relationships and implementation partner engagements during modernization phases
• Define and track platform SLAs, data quality metrics, and team performance indicators
• Establish measurable goals for data onboarding speed, pipeline reliability, and self-service adoption
• Monitor infrastructure costs and optimize cloud spending through effective resource management
• Ensure audit-ready documentation, disaster recovery capabilities, and enterprise security controls
• Lead incident response for critical data platform issues with clear communication and rapid resolution

Benefits

• medical, dental, and vision plans, disability, life insurance, parenting benefits, flexible spending account options, generous vacation time, referral bonuses, professional development, and a 403(b) plan

What This Job Offers

• Job Type: Full-time
• Career Level: Executive