Data Modeler

· More than 8+ years of experience in various data architecture and engineering roles within data & analytics

· Collaborate with stakeholders to understand and document data requirements, business rules, and objectives for the data platform.

· Design and develop conceptual, logical, and physical data models that accurately represent the organization's data assets and support its business needs.

· Ensure designs meet documented objectives for reliability, scalability, supportability, user experience, security, governance, performance and more

· Implement data modeling best practices, including normalization, denormalization, and indexing, to ensure data integrity, performance, and scalability.

· Work closely with data engineers and architects to integrate data models into the overall platform architecture, ensuring efficient data processing and storage.

· Evaluate and recommend appropriate data storage technologies and database management systems based on project requirements and constraints.

· Drive data modeling automation to optimize solutions time to market, increase solutions transparency and overall quality as well as code portability

· Collaborate with data analysts to understand analytical requirements and ensure that data models support effective data analysis and reporting.

· Communicate effectively with technical and non-technical stakeholders to present and explain data models, design decisions, and recommendations.

· Good understanding of key data modeling concepts & patterns related to data systems architecture.

· Strong years of hands-on relational, dimensional, and/or analytic experience (using RDBMS, dimensional, NoSQL data platform technologies, and ETL and data ingestion protocols).

· Experience with data warehouse, data lake, and enterprise big data platforms in multi-data-center contexts required.

· Implement business and IT data requirements through new data strategies and designs across all data platforms (relational, dimensional, and NoSQL) and data tools (reporting, visualization, analytics, and machine learning).

· Work with business and application/solution teams to implement data strategies, build data flows, and develop conceptual/logical/physical data models

· Identify the architecture, infrastructure, and interfaces to data sources, tools supporting automated data loads, security concerns, analytic models, and data visualization.

· Hands-on modeling, design, configuration, installation, performance tuning, and sandbox POC.

· Work proactively and in dependent