Cloud Data Architect

Data Ideology•Pittsburgh, PA

6d•Remote

About The Position

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 www.dataideology.com. 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.

Requirements

8+ years of experience in data architecture, data modeling, or cloud data engineering, with demonstrated ownership of architecture decisions.
Hands-on experience designing and implementing cloud data solutions using Snowflake, Azure, AWS, and/or Databricks.
Deep understanding of distributed systems, data architecture, and modern cloud infrastructure.
Experience with Lakehouse architecture and platforms (Delta Lake, Apache Iceberg, Apache Hudi).
Demonstrated success designing semantic data models for reporting and analytics at scale.
Experience leading or supporting large-scale data migrations, from discovery through cutover, and building systems from concept through production.
Experience supporting low-latency or high-volume data environments is highly desirable.
Strong grounding in modern data warehousing, ELT/ETL, and cloud architecture best practices.
Proven ability to navigate ambiguity, influence technical direction, and drive clarity across cross-functional teams, balancing strategic vision with hands-on execution.
Excellent communication, presentation, and stakeholder management skills.

Nice To Haves

Deep experience with data governance, metadata management, MDM, and data quality frameworks.
Familiarity with data catalog tools (e.g., Purview, Collibra, Alation).
Track record supporting enterprise data modernization, migration, or cloud transformation initiatives.

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.
Mentor junior architects and data management staff, and translate complex technical concepts into clear, business-friendly language for technical and non-technical audiences alike.