Data Architect

Job Title: Data Warehouse Architect / Associate Technical Architect

Location: Any

Job Type: Full-time

About Us

We are a specialized IT and AI software development company dedicated to transforming the educational landscape. We partner with higher education institutions and EdTech organizations in the USA to build cutting-edge, scalable AI and IT solutions. We pride ourselves on our Agile mindset, technical excellence, and commitment to delivering products that enhance educational outcomes and operational efficiency.

Role Summary

We are seeking a visionary Data Warehouse Architect to design and build the robust data infrastructure required to power our next-generation AI solutions. In this role, you will lead the strategic design, implementation, and operational scalability of enterprise data warehouses and data lakes for our US higher education clients. You will be responsible for unifying siloed educational data into a secure, highly performant "single source of truth" that enables advanced data analytics, machine learning models, and AI-driven insights.

Key Responsibilities

1. Architectural Design & Strategy

• Design, implement, and manage scalable, cloud-based data warehouse and data lake architectures (e.g., Snowflake, AWS Redshift, Google BigQuery, or Azure Synapse).
• Define the overall data architecture strategy, including data modeling (Star schema, Snowflake schema, Data Vault), data storage, and data retrieval processes optimized for heavy analytical workloads.

2. Data Integration & Pipeline Engineering (ETL/ELT)

• Architect robust, automated ETL/ELT pipelines to ingest, clean, and transform data from diverse EdTech systems, including Learning Management Systems (LMS like Canvas, Blackboard), Student Information Systems (SIS like Banner, Workday), and CRM platforms.
• Ensure pipelines are highly resilient, scalable, and capable of handling both batch and near-real-time data streaming.

3. Enabling AI & Advanced Analytics

• Collaborate closely with Data Scientists, Prompt Engineers, and AI Developers to ensure the data architecture supports complex AI use cases (e.g., predictive student success modeling, generative AI knowledge retrieval, and performance analytics).
• Optimize database performance, query execution, and compute resource allocation to support high-speed AI data processing.

4. Data Governance, Security & Compliance

• Establish and enforce data governance frameworks, ensuring data quality, consistency, and master data management.
• Design architectures that strictly adhere to US data privacy and security standards, specifically FERPA (Family Educational Rights and Privacy Act), ensuring sensitive student data is encrypted, anonymized, and access-controlled.

5. Agile Leadership & Collaboration

• Work within Agile frameworks alongside Product Owners and Scrum teams to break down architectural epics into deliverable user stories.
• Mentor data engineers and developers on best practices for database design, SQL optimization, and scalable data engineering.

Required Qualifications

• Experience: 11+ years of experience in data engineering and architecture, with at least 5 years successfully architecting cloud-native data warehouses.
• Technical Expertise: Deep hands-on experience with modern cloud data platforms (Snowflake, AWS, GCP, or Azure) and ETL/ELT orchestration tools (e.g., dbt, Apache Airflow, Matillion, Fivetran).
• Database & Modeling: Expert-level SQL skills and comprehensive knowledge of relational, NoSQL, and columnar databases. Strong proficiency in advanced data modeling techniques.
• AI/ML Infrastructure: Experience building data architectures specifically tailored to feed machine learning models, BI tools (Tableau, PowerBI), and AI applications.
• Agile Mindset: Proven experience working in an Agile/Scrum environment, participating in sprint planning, and delivering incremental architectural value.

Preferred Qualifications

• Domain Knowledge: Previous experience working with Higher Education data, EdTech platforms, or familiarity with educational data standards (e.g., Ed-Fi, CEDS, LTI).
• Certifications: Relevant cloud architecture certifications (e.g., AWS Certified Data Analytics, Snowflake SnowPro Core/Advanced, Microsoft Certified: Azure Data Engineer).
• Programming: Proficiency in Python or Scala for data engineering and scripting.