Data Modeler

The data modeler designs, implements, and documents data design patterns and data modeling solutions, which include the use of relational, dimensional, and NoSQL databases. These solutions support enterprise-wide data products implementation and enabling all forms of data dependent use-cases.

Key Responsibilities of Data Modeler:

• Be responsible for Creating / Maintaining / Optimizing conceptual, logical, and physical data models, the implementation of operational data store (ODS), data marts, and data lakes on target platforms (SQL/NoSQL) using best practices to ensure high data quality and reduced redundancy.
• Implement business and IT data requirements through new data strategy and designs across all data platforms (relational, dimensional, and NoSQL) and relevant data tools (reporting, visualization, analytics, and machine learning).
• Defines and governs data modeling and design standards, tools, best practices, and related development for enterprise data models.
• Managing the enhancements / expansion of existing data models and the optimization of data query performance via best practices.
• Working closely with Data Domain Specialists & Data Product Owners for the understanding of Data Product level functional specifications, obtaining the business context and consumption patterns around the data.
• Creating Structure / Schema for Target Data as per business requirements (nature of data + consumption patterns) by leveraging business context & data product functional specifications.
• Performing Data Profiling as may be required to arrive at future proof data model design for Data Products.
• Providing Technical Specifications to development team (Data Engineering & BI teams) as per final target schema for data (functional specifications are converted to fit into target structure).
• Generating DDL (Create Table) Scripts using Data Modeling Tool, working with Technology Engineers to create the required database objects onto the respective database platform and maintaining the required enhancements.
• Works proactively and independently to address project requirements and articulate issues/challenges to reduce project delivery risks.
• Working collaboratively with all involved teams and contributing to the advancement of data strategy operationalization.

Skills Required:

• Bachelors/ master's degree in information management, Computer Science & Engineering, or equivalent degree from an accredited academic institution or related experience.
• Preferred Banking domain knowledge and multi-market experience.
• Minimum 5+ years of hands-on relational, dimensional modeling, and/or analytic experience (using RDBMS, dimensional, NoSQL data platform technologies, and ETL and data ingestion protocols).
• Experience and knowledge across different design patterns for Data Repositories such as Data Warehouse, Data Lake, Data Lakehouse, Data Mesh, Data Fabric and enterprise big data platforms including a full understanding of end-to-end data flow cycles.
• Core Skills Required:
• Expertise in data modeling principles / methods including conceptual, logical & physical Data Models.
• Skills/Conceptual knowledge required to create optimal data models - Star & Snowflake Schemas, Data Vault Methodologies, Dimensional Modeling techniques (Slowly Changing, Fast Changing, Snapshot methodology, Degenerated dimensions etc.), Normalization & Denormalization, Surrogate Key Concepts etc.
• Technical Skills Required:
• Hands-on expertise on data modeling tools such as (SAP Power Designer, ERWin, ER/Studio etc.)
• Knowledge in Industry Reference data models: IBM BFMDW, Teradata FSLDM, SAP FSDM etc.
• Best Practice / Design Standard Skills Required:
• Naming standards for Schemas, Data Objects & Data Attributes.
• Identifying best fit data type & length for each data attribute as part of physical data model.
• Leveraging common Master & Reference Data.
• Ensures no redundancy in terms of data objects design based on nature of data (Master / Transactional / Reference).
• Ensuring Data Objects are designed to provide long-term stability.
• Robust knowledge of data, systems and querying tools like SAS/SQL and proven ability to quickly learn new systems and data environments.
• Preferred knowledge across all key facets of Data Management (Data Warehousing, BI, Data Governance, Data Quality, Master/Reference Data Management, Data Privacy Management, Application side Data Management and External Data Assets Management).
• Preferred knowledge in HADOOP, Oracle, PostgreSQL & SAP HANA database technology platforms.
• Preferred knowledge in interacting with Data Governance tools (Informatica AXON-EDC-DEQ).

Collaborative team player with strong stakeholder management skills, who can think creatively and strategically while building cross-functional and cross-divisional relationships.

Seniority level: Mid-Senior level

Employment type: Full-time

Job function: Information Technology

Industries: IT Services and IT Consulting