SQL Data Modeller/ Architect Job Description
The SQL Data Modeller/ Architect is responsible for the strategic design, development, and maintenance of scalable, secure, and high-performing data architectures and database systems, primarily within a SQL environment. This role involves translating business requirements into technical data solutions, ensuring data integrity, and optimizing data accessibility for various applications and analytical needs.
Experience in finance or book keeping domain will be a plus.
Key Responsibilities:
- Data Architecture Design: Design and develop conceptual, logical, and physical data models for relational databases, data warehouses, and other data stores using SQL-based technologies.
- Database Development & Optimization: Create, implement, and optimize database structures, schemas, stored procedures, functions, and views in SQL Server or other relevant SQL platforms.
- Data Integration & ETL: Design and implement robust Extract, Transform, Load (ETL) processes to integrate data from diverse sources into the data architecture.
- Performance Tuning: Analyze and optimize database performance through query tuning, indexing strategies, and database configuration adjustments.
- Data Governance & Security: Define and enforce data governance policies, security measures, and compliance standards (e.g., GDPR, HIPAA) for SQL databases.
- Collaboration & Support: Work closely with data engineers, data scientists, software developers, and business stakeholders to understand data requirements and provide technical guidance.
- Documentation: Create comprehensive documentation for data architecture, data models, technical specifications, and data flow diagrams.
- Technology Evaluation: Evaluate and recommend new database technologies, tools, and best practices to enhance the data infrastructure.
- Technical Expertise:
- In-depth expertise in SQL and proficiency with relational database management systems (RDBMS) like SQL Server, Oracle, MySQL, or PostgreSQL.
- Strong understanding of data modeling principles and techniques (e.g., Kimball, Inmon).
- Experience with ETL tools and processes.
- Knowledge of data warehousing concepts and OLAP.
- Familiarity with cloud-based data platforms (e.g., Azure SQL Database, AWS RDS) is a plus.
- Analytical & Problem-Solving Skills: Strong analytical capabilities to identify data-related issues and develop effective solutions.
- Communication: Excellent communication skills to effectively convey complex technical information to both technical and non-technical audiences.
- Collaboration: Ability to work effectively in a team environment between onshore and offshore and collaborate with cross-functional teams is critical.
