Job
Description
Job Summary We are seeking a seasoned Data Modeller with deep expertise in designing, implementing, and optimizing data models for both OLTP (Online Transaction Processing) and OLAP (Online Analytical Processing) systems. The ideal candidate will have hands-on experience working with Google Cloud Platform (GCP) database services such as AlloyDB, CloudSQL, and BigQuery, and will leverage strong data modeling and performance tuning skills to deliver scalable, high-performing enterprise data solutions. Key Responsibilities: Design and develop conceptual, logical, and physical data models for OLTP and OLAP systems, ensuring alignment with business goals and technology roadmaps. Architect end-to-end enterprise data warehouse and operational data store solutions with best practices in dimensional and normalized modeling (Inmon, Kimball, 3NF). Implement database optimization strategies including indexing, partitioning, and data sharding to enhance performance, scalability, and availability. Lead cloud migration and modernization initiatives, focusing on GCP services such as AlloyDB, CloudSQL, and BigQuery to support hybrid and cloud-native data architectures. Collaborate closely with data engineers, BI developers, and business stakeholders to translate complex business requirements into robust data models and schemas. Utilize advanced data modeling tools such as DBSchema, ERWin, or Visio to document and manage database schemas and metadata. Establish and enforce data governance, data quality, and metadata management frameworks to ensure data accuracy and compliance. Stay abreast of emerging trends and technologies in data architecture, cloud databases, and analytics to continuously improve data platform capabilities. Required Skills and Qualifications: Bachelors degree in Computer Science, Information Technology, or related field; Masters preferred. 10+ years of experience in data modeling and architecture for OLTP and OLAP environments. Strong proficiency in conceptual, logical, and physical data modeling techniques and methodologies (3NF, Inmon, Kimball). Extensive hands-on experience with data modeling tools such as DBSchema, ERWin, or equivalent. Expertise in indexing, partitioning, query optimization, and data sharding for high-volume transactional and analytical databases. Proven experience designing and optimizing cloud databases on Google Cloud Platform (AlloyDB, CloudSQL, BigQuery). Strong SQL skills with proficiency in PL/SQL, T-SQL, and performance tuning. Familiarity with ETL frameworks and BI tools such as SSIS, Power BI, Tableau, and Azure Data Factory is a plus. Excellent problem-solving skills with keen attention to detail and data quality. Strong communication, collaboration, and stakeholder management skills. Experience or knowledge of financial services or mutual fund industry data models is advantageous. Familiarity with Agile/Scrum methodologies.
