Data Platform Architect (26-27)

IDEA Public Schools•Weslaco, TX

23h•$98,200 - $115,900•Hybrid

About The Position

Data Platform Architect This is a vacancy for the 26-27 school year with a target start date of July 1, 2026 Mission: The Data Platform Architect is a senior technical leader responsible for ensuring the long-term coherence, scalability, and integrity of IDEA’s modern data platform. This role provides deep architectural expertise across cloud data platforms, pipelines, models, and governance to support IDEA’s transition to a Snowflake-based lakehouse and modern analytics stack. This is a high-impact, senior individual contributor role that will lead through architectural depth, technical judgment, and design stewardship, ensuring that platform decisions made today remain durable, secure, and cost-effective over years of growth. The Data Platform Architect operates in close partnership with the Managing Director of Data Platform & Engineering, translating platform strategy into architectural patterns, standards, and guardrails that enable teams to move quickly without creating long-term risk. Supervisory Responsibilities: Not a Supervisory role Location: This is a full-time (remote/on-site) 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 to team meetings, leadership gatherings, regional offices, and occasional vendor/partner locations during critical implementation phases. What You’ll Do – Accountabilities Essential Duties: Define and maintain reference architectures for IDEA’s modern data platform, including Snowflake lakehouse patterns, ELT workflows, semantic layers, and data governance integration. Establish architectural standards and design principles that ensure scalability, reliability, security, and cost efficiency across all data domains. Serve as the architectural authority for complex, high-impact design decisions, identifying tradeoffs and long-term implications. Proactively identify architectural risks related to performance, cost, security, compliance, and technical debt. Advise leadership on mitigation strategies and design alternatives before risks materialize. Ensure architectural decisions balance speed with durability in a multi-state, high-paced environment. Lead architecture and design reviews for data platform initiatives, pipelines, and data products. Additional Duties and Responsibilities: Ensure consistent use of approved patterns while allowing for innovation where appropriate. Elevate engineering quality through guidance, documentation, and feedback rather than direct execution. Translate the enterprise platform strategy into actionable architectural guidance for engineers and analytics teams. Define reusable patterns for ingestion, transformation ( dbt ), testing, observability, and semantic modeling. Support adoption of modern data practices including ELT-first design, automated testing, lineage tracking, and self-service analytics enablement. Mentor data platform engineers and analytics engineers on architectural thinking and system design. Contribute to the development of architectural literacy across the data organization. Help teams understand why architectural standards exist, not just what they are. Partner with contracted services, as needed, to speed maturity. Knowledge and Skills – Competencies Make Strategic Decisions: This team member fosters an inclusive decision-making environment by encouraging diverse perspectives, managing disagreements constructively, and creating space for all voices to be heard. They clearly communicate final decisions, providing context and anticipated impact—even when choices are difficult or unpopular. Manage Work and Teams: This team member leads cross-functional coordination to align efforts with strategic goals, optimizing resource use and minimizing silos. They build accountability frameworks, monitor key performance indicators to guide adjustments, and mentor emerging leaders, while implementing scalable systems that enhance efficiency and team effectiveness. Grow Self and Others: This team member uses data to assess development needs and designs learning opportunities that align with team goals and individual career growth. They model a growth mindset by being open about their own development and ensure that both personal and team-led learning initiatives are impactful and well-aligned with organizational priorities. Build a Culture of Trust : This team member fosters a team culture where individuals genuinely care for one another both personally and professionally. They lead with transparency, encourage open communication, including healthy conflict—and promote reliability and consistency, while regularly seeking and responding to team feedback to enhance the collective experience. Communicate Deliberately: This team member leads inclusive discussions that surface obstacles and drive actionable solutions, ensuring all voices are heard. They communicate key information clearly across multiple channels and establish feedback loops that promote open dialogue, collaboration, and continuous improvement.

Requirements

Cloud data platform architecture
SQL and data modeling
ELT frameworks and dbt
Data governance, lineage, and security patterns
Architectural documentation and design review
Iceberg or other modern table formats
Bachelor’s degree in Computer Science , Information Systems, or related field ( Master’s preferred)
8+ years designing and supporting enterprise data platforms
Deep experience with cloud data architectures (Snowflake, Databricks, or comparable platforms)
Strong background in dimensional modeling, ELT pipelines, and analytics engineering patterns
Proven experience guiding architecture in complex, evolving environments
Demonstrated ability to influence without direct authority
Prolonged periods working on a computer and in virtual meetings
Ability to travel domestically via car and air travel
Occasional evening/weekend work during critical deployments or incidents
Flexibility for different time zones when collaborating with distributed teams

Nice To Haves

Data quality and observability tooling
Semantic layers and metrics stores
Data mesh or federated analytics patterns

Responsibilities

Define and maintain reference architectures for IDEA’s modern data platform, including Snowflake lakehouse patterns, ELT workflows, semantic layers, and data governance integration.
Establish architectural standards and design principles that ensure scalability, reliability, security, and cost efficiency across all data domains.
Serve as the architectural authority for complex, high-impact design decisions, identifying tradeoffs and long-term implications.
Proactively identify architectural risks related to performance, cost, security, compliance, and technical debt.
Advise leadership on mitigation strategies and design alternatives before risks materialize.
Ensure architectural decisions balance speed with durability in a multi-state, high-paced environment.
Lead architecture and design reviews for data platform initiatives, pipelines, and data products.
Ensure consistent use of approved patterns while allowing for innovation where appropriate.
Elevate engineering quality through guidance, documentation, and feedback rather than direct execution.
Translate the enterprise platform strategy into actionable architectural guidance for engineers and analytics teams.
Define reusable patterns for ingestion, transformation ( dbt ), testing, observability, and semantic modeling.
Support adoption of modern data practices including ELT-first design, automated testing, lineage tracking, and self-service analytics enablement.
Mentor data platform engineers and analytics engineers on architectural thinking and system design.
Contribute to the development of architectural literacy across the data organization.
Help teams understand why architectural standards exist, not just what they are.
Partner with contracted services, as needed, to speed maturity.