Role Overview:

We are looking for an experienced Data Architect with strong expertise in Microsoft SQL Server, enterprise data architecture, and data modelling, along with good functional understanding of ERP Finance, Procurement, Sales, and Compensation processes.

The role will be responsible for designing scalable data solutions, defining enterprise data models and integration strategies, and working closely with business and technology teams to ensure data architecture effectively supports operational applications, reporting, and analytics.

Key Responsibilities:

- Design and maintain conceptual, logical, and physical data models for enterprise applications and data platforms.

- Define enterprise data architecture, data structures, relationships, standards, naming conventions, and integration patterns.

- Provide technical leadership for Microsoft SQL Server database architecture and design.

- Design and review tables, views, stored procedures, indexes, keys, constraints, and other database objects.

- Optimize SQL queries, database structures, and data access patterns to improve performance, scalability, and reliability.

- Define data integration requirements and architecture for ETL/ELT pipelines across ERP applications, data platforms, and reporting environments.

- Develop and review source-to-target mappings, transformation rules, and data-flow specifications.

- Ensure consistency, integrity, and traceability of data across source systems, operational applications, warehouses, and reporting platforms.

- Design data models that support transactional applications, data warehouses, analytics, and management reporting.

- Work closely with Business Analysts, Application Developers, Data Engineers, BI teams, and enterprise architects to translate business requirements into scalable data solutions.

- Provide data architecture guidance for integration between ERP systems and downstream reporting or analytical platforms.

- Ensure implementation of appropriate data quality, security, governance, metadata, and data lineage practices.

- Review existing data architectures and identify opportunities for modernization, simplification, and performance improvement.

- Support data-related solution design, technical reviews, and architecture decision-making across projects.

- Provide technical guidance, mentoring, and design support to SQL developers and data engineering teams.

- Maintain architecture documentation, data models, integration specifications, standards, and technical guidelines.

Required Skills & Experience:

- 12 - 15 years of experience in Data Architecture, Database Architecture, Data Engineering, or a related technology domain.

- Strong hands-on expertise in Microsoft SQL Server and enterprise database architecture.

- Strong experience in conceptual, logical, and physical data modelling.

- Strong understanding of relational database design, normalization, indexing, query optimization, and performance tuning.

- Experience with tables, views, stored procedures, functions, indexes, constraints, and complex SQL development.

- Strong understanding of ETL/ELT, data integration, source-to-target mapping, data transformation, and data-flow architecture.

- Experience designing data solutions for operational applications, data warehouses, reporting platforms, and analytics environments.

- Good understanding of data quality, security, governance, metadata, and lineage.

- Strong stakeholder-management and communication skills, with the ability to work across business and technical teams.

- Proven experience providing technical leadership and mentoring to database, SQL, and data engineering teams.

- Good understanding of SDLC, enterprise architecture, and solution-design practices.

Functional / Domain Knowledge:

- Good functional understanding of ERP Finance processes.

- Good understanding of Procurement and Purchase-to-Pay processes.

- Good understanding of Sales and Order-to-Cash processes.

- Exposure to Compensation and related HR/enterprise processes.

- Ability to understand business process flows and translate them into effective data structures and reporting solutions.