Job
Description
As a Data Architect, you will be responsible for designing and implementing high-performance database configurations using Microsoft SQL Server and MongoDB. Your key responsibilities will include: - Developing and managing ETL processes with SaaS services, data lakes, and data sources such as Dremio and Databricks. - Collaborating with reporting and analytics teams to integrate systems like Power BI, Qlik, and Crystal Reports. - Providing strategic direction for long-term data strategy and architecture. - Identifying and implementing performance fixes and scalability solutions for existing systems. - Troubleshooting and resolving performance issues in database systems. - Leading hands-on implementation of both SQL Server and MongoDB. - Managing security, user roles, and access controls within database systems. - Providing guidance and direction to teams on data strategy and architecture best practices. - Re-engineering existing databases based on load requirements and implementing performance improvements. - Documenting database designs, ER diagrams, and publishing functional domain documentation. Your key skills should include: - Microsoft SQL Server Expertise: - Proficient in writing and optimizing stored procedures, triggers, and complex queries. - Strong understanding of indexes and their impact on performance. - Ability to analyze and optimize execution plans for query performance. - Experience in high-performance schema design using both bottom-up and top-down approaches. - Database Design and Performance: - Expertise in re-engineering existing databases to enhance performance based on load analysis. - Strong understanding of data schema design and ACID principles. - Hands-on experience with SQL and NoSQL database implementations, particularly with MongoDB. - Good understanding of security best practices and user management in database systems. - Cloud and Integration: - Good understanding of AWS cloud services related to database management. - Experience with PaaS, SaaS, and IaaS concepts in both on-premises and cloud environments. To be eligible for this role, you should have: - 9-14 years of experience in data architecture, database design, and implementation. - Strong experience with ETL processes and data integration using SaaS services. - Proficiency in reporting and analytics tools such as Power BI, Qlik, and Crystal Reports. - A strategic mindset with the ability to develop and execute long-term data strategies. - Excellent communication and leadership skills, with the ability to direct teams effectively. As a Data Architect, you will be responsible for designing and implementing high-performance database configurations using Microsoft SQL Server and MongoDB. Your key responsibilities will include: - Developing and managing ETL processes with SaaS services, data lakes, and data sources such as Dremio and Databricks. - Collaborating with reporting and analytics teams to integrate systems like Power BI, Qlik, and Crystal Reports. - Providing strategic direction for long-term data strategy and architecture. - Identifying and implementing performance fixes and scalability solutions for existing systems. - Troubleshooting and resolving performance issues in database systems. - Leading hands-on implementation of both SQL Server and MongoDB. - Managing security, user roles, and access controls within database systems. - Providing guidance and direction to teams on data strategy and architecture best practices. - Re-engineering existing databases based on load requirements and implementing performance improvements. - Documenting database designs, ER diagrams, and publishing functional domain documentation. Your key skills should include: - Microsoft SQL Server Expertise: - Proficient in writing and optimizing stored procedures, triggers, and complex queries. - Strong understanding of indexes and their impact on performance. - Ability to analyze and optimize execution plans for query performance. - Experience in high-performance schema design using both bottom-up and top-down approaches. - Database Design and Performance: - Expertise in re-engineering existing databases to enhance performance based on load analysis. - Strong understanding of data schema design and ACID principles. - Hands-on experience with SQL and NoSQL database implementations, particularly with MongoDB. - Good understanding of security best practices and user management in database systems. - Cloud and Integration: - Good understanding of AWS cloud services related to database management. - Experience with PaaS, SaaS, and IaaS concepts in both on-premises and cloud environments. To be eligible for this role, you should have: - 9-14 years of experience in data architecture, database design, and implementation. - Strong experience with ETL processes and data integration using SaaS services. - Proficiency in reporting and analytics tools such as Power BI, Qlik, and Crystal Reports. - A st
