Data Ideology
At DI, we provide Data & Analytics expertise to drive measurable business outcomes, often solving complex business problems for our clients. Our data analytics advisory services enable our customers to transform data into insights by driving a culture of empowerment and ownership of results. Our team consists of highly motivated individuals passionate about learning, understanding, collaborating, and intellectually curious. For more information about Data Ideology, visit .

Cloud Data Architect
We are always looking to connect with top talent! We are seeking a skilled and collaborative Cloud Data Architect to help drive ongoing data modernization efforts. This role is responsible for designing and enabling modern cloud data platforms, integrating enterprise systems, and building semantic data models that support critical business functions across the organization. If you're passionate about cloud architecture, scalable data solutions, and helping organizations transform their data ecosystems, we'd love to connect with you.

Key Responsibilities

• Own the architecture for cloud-native data platforms, including Lakehouse designs (Delta Lake, Iceberg, Databricks, or Microsoft Fabric) that support reporting, analytics, and BI.
• Design scalable data models supporting enterprise platforms, including ERP, financial, operational, and project management systems.
• Lead modernization initiatives for legacy data environments, including migration strategy, data mapping/transformation, reconciliation, and cutover to production.
• Build frameworks for real-time and near real-time data ingestion and processing, alongside batch pipelines (ELT/ETL).
• Drive decisions across storage, orchestration, data quality, reliability, and performance.
• Define semantic data models that enable self-service analytics and consistent reporting, in coordination with data governance, metadata management, and master data management (MDM) standards.
• Partner with business and technical stakeholders across functional areas to prioritize requirements and translate them into architectural decisions.
• Support secure, governed data access in coordination with Identity and Access Management (IAM) teams.
• Evaluate emerging technologies, including AI, and identify opportunities to apply them within the data ecosystem; help shape the long-term technical roadmap.