Data Modeller

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About The Role

Data Modeller

OLTP and OLAP systems

Google Cloud Platform (GCP)

conceptual, logical, and physical data modelling

CloudSQL

BigQuery

data modelling tools like DBSchema

Key Responsibilities

• Design and develop conceptual, logical, and physical data models for structured and semi-structured data.
• Implement data models optimized for both transactional (OLTP) and analytical (OLAP) use cases.
• Define and apply indexing, partitioning, and data sharding strategies for performance and scalability.
• Collaborate with data engineers and developers to ensure models support reporting, analytics, and application requirements.
• Work with GCP data services like AlloyDB, CloudSQL, and BigQuery to design efficient cloud-native data solutions.
• Perform data profiling, quality checks, and support schema evolution and impact analysis.
• Use data modelling tools such as DBSchema (preferred) or other industry-standard tools.
• Tune database designs for near real-time reporting and performance optimization.
• Document metadata, lineage, and model specifications for team consumption and governance.
  

Required Skills

• 6–9 years of experience in data modelling for enterprise systems.
• Expertise in OLTP/OLAP modelling, indexing, and database performance tuning.
• Hands-on experience with GCP data platforms – CloudSQL, AlloyDB, BigQuery.
• Proficiency in using data modelling tools (preferably DBSchema).
• Strong knowledge of partitioning, sharding, and database schema optimization.
• Good understanding of data governance, lineage, and best practices.
  

Nice To Have

• Functional knowledge or domain exposure to the mutual fund or financial services industry.
• Experience with real-time analytics and streaming data environments.
• Familiarity with other cloud platforms (AWS, Azure) and their data services.
  

What We Offer

• Opportunity to work on enterprise-level, cloud-first data architecture.
• Exposure to modern data platforms and modeling strategies on GCP.
• A collaborative, growth-focused work culture.
• Competitive salary and learning opportunities, including cloud certifications.
• Work with a team solving complex data problems in real-world financial domains