Staff Data Architect

About the role

At Apptegy, we are more than a tech company; we are partners dedicated to transforming how schools communicate and shape the future of education. Your work here will directly empower districts to share their stories, engage their communities, and celebrate student success. We're a team of thoughtful, high-performing individuals committed to making a tangible impact. If you're looking for a dynamic environment where you'll be supported with exceptional mentorship and resources to grow your career, come build with us. Apptegy is building the data platform that powers decision-making across a high-growth SaaS business. As our Staff Data Architect, you will define and own the enterprise data architecture that enables the business to operate with confidence at scale. This includes how data is ingested, modeled, governed, secured, and consumed across the organization, with Snowflake at the core of the platform. This is a high-impact, high-autonomy individual contributor role reporting directly to the VP of Data & Analytics. You will serve as the technical authority for how data is structured and used across the company, setting the architectural vision for the Business Data Platform and guiding the standards that allow a small, high-performing team to move quickly without compromising quality, governance, or long-term scalability. The right person for this role brings deep Snowflake expertise, strong architectural judgment, and a clear point of view on modern data platform design. They are equally comfortable defining long-range strategy, making consequential build-versus-buy decisions, and working hands-on with engineers to shape implementation details. This person will also help define how the platform serves as the enterprise context layer for AI, ensuring data is enriched, well-modeled, and reliable enough to support LLM, RAG, and agent-based use cases across the business.

Responsibilities

• Architecture & Platform Design
• Define and evolve the enterprise data architecture across ingestion, storage, transformation, semantic modeling, and consumption layers, with Snowflake as the core platform.
• Design and own the medallion architecture across Bronze, Silver, Gold, and Semantic layers, establishing clear standards for schema design, object naming, access patterns, and layer boundaries.
• Lead semantic model strategy by defining how key business entities, metrics, and KPIs are represented in Snowflake and surfaced through BI tools.
• Drive architectural decisions across the modern data stack, including ingestion through Fivetran, transformation through Coalesce and related conventions, and BI delivery through Tableau, ensuring cohesion across the full platform.
• Identify and resolve performance, scalability, and cost-efficiency challenges in Snowflake, including query optimization, clustering strategy, virtual warehouse sizing, and storage management.
• Design the platform to serve as a reliable enterprise context layer for AI by establishing patterns for metadata enrichment, semantic data modeling, contextual retrieval, and curated data products that support LLM, RAG, and AI agent use cases.
• Governance & Data Quality
• Establish and enforce data governance standards, including naming conventions, data contracts, PII handling, access controls, lineage expectations, and documentation practices.
• Define the organization's approach to data observability, including freshness monitoring, anomaly detection, pipeline reliability standards, SLA expectations, and incident response patterns.
• Partner with security and other stakeholders to ensure the data platform meets compliance, risk, and regulatory requirements.
• Build and maintain architectural reference documentation, data flow diagrams, decision records, and the data dictionary that support platform clarity and long-term maintainability.
• Technical Leadership & Strategy
• Act as the senior technical voice on the data team, guiding architectural decisions across active initiatives, resolving ambiguity, and setting long-term direction for the platform.
• Evaluate and recommend new tools, platforms, and approaches, leading build-versus-buy decisions with clear trade-off analysis and strong technical rationale.
• Partner closely with the VP of Data & Analytics on roadmap planning, prioritization, and strategic vendor relationships, including Snowflake, Tableau, Fivetran, and related platform partners.
• Provide hands-on architectural guidance to Data Engineers and Analytics Engineers through design reviews, standards setting, and active support on complex implementation work.
• Communicate architectural vision, platform strategy, and technical decisions clearly to engineering leaders, business stakeholders, and executive partners.
• Cross-Functional Partnership
• Collaborate with stakeholders across the company to understand evolving data requirements and translate them into scalable, well-modeled, maintainable solutions.
• Partner with the broader enginee

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