Data Architect / Enterprise Data Architect / Database Architect- Remote

We are seeking an experienced Data Architect / Enterprise Data Architect / Database Architect to design, build, and govern scalable data platforms across cloud and on-prem environments. The ideal candidate will have strong expertise in SQL, Azure, Oracle, ETL, and AWS, with a proven ability to design enterprise-level data architectures that support analytics, reporting, and operational systems.

This role will work closely with business stakeholders, data engineers, application teams, and cloud architects to define data strategy, standards, and best practices.

• Design and maintain enterprise-level data architecture and data models.

• Lead architecture for cloud and hybrid data platforms using Azure and AWS.

• Architect and optimize relational and non-relational databases, including Oracle and SQL-based systems.

• Define data integration patterns using ETL/ELT tools and frameworks.

• Establish data governance, data quality, and metadata management standards.

• Partner with application and analytics teams to support reporting, BI, and advanced analytics use cases.

• Provide technical leadership and guidance to data engineering and development teams.

• Perform performance tuning, capacity planning, and cost optimization.

• Define data security, access control, and compliance best practices.

• Strong hands-on experience with SQL and database architecture/design.

• Deep experience with Oracle databases (architecture, performance tuning, HA/DR).

• Experience with Azure data services (e.g., Azure SQL, Synapse, Data Factory, Data Lake).

• Experience with AWS data services (e.g., RDS, Redshift, S3, Glue, Athena).

• Solid experience with ETL/ELT tools and data integration frameworks.

• Expertise in data modeling (conceptual, logical, physical).

• Strong understanding of data warehousing and lakehouse architectures.

• Experience designing scalable, high-availability, and fault-tolerant data systems.

• Knowledge of data governance, data quality, and master data management concepts.