Data Modeler

📋 Description

• • As a Data Modeler at Signatureglobal India Private Limited, you will play a pivotal role in shaping the foundation of our data landscape. This mid-level position is designed for an individual with a strong command of 3NF/relational data modeling principles, who is also adept at supporting broader data management functions. You will be instrumental in designing, building, and evolving governed data models that are critical for powering our Advisory products and informing strategic decision-making.
• • Your core responsibility will involve the meticulous design, maintenance, and versioning of conceptual, logical, and physical data models. This includes adhering to strict 3NF normalization standards and meticulously documenting naming conventions and established standards to ensure consistency and clarity across all data assets.
• • You will strategically apply denormalization patterns where necessary, carefully balancing the need for optimized analytics and downstream consumption with the imperative to preserve data quality and maintain clear data lineage. This nuanced approach ensures that our data is both performant and trustworthy.
• • A significant aspect of your role will be the proficient use of ERWin, a leading data modeling tool. You will leverage ERWin to capture entities, attributes, relationships, indexes, and constraints. Furthermore, you will enrich these models with detailed metadata and actively steward the model repository, ensuring its accuracy and completeness.
• • From ERWin, you will generate comprehensive stakeholder review reports and publish detailed model documentation. You will also be responsible for creating and reviewing Data Definition Language (DDL) generated by ERWin, and preparing Data Manipulation Language (DML) scripts for reference data, ensuring the integrity and usability of our data structures.
• • Beyond modeling, you will actively engage in data profiling and quality assurance. This involves performing both manual and tool-assisted data profiling using SQL and other available tools. You will meticulously summarize data distributions, identify anomalies, validate keys, and assess referential integrity. The insights gained from this profiling will directly feed into data quality scorecards and inform remediation actions, driving continuous improvement in our data assets.
• • The role also encompasses defining source-to-target mappings at both the table and column levels. This includes specifying joins, keys, transformations, and data rules. You will maintain these mapping packs diligently, ensuring they are clear and ready for engineering handoff, facilitating seamless data integration processes.
• • You will determine appropriate load sequences for master and reference data across normalized structures, authoring and reviewing insert/update sequences for batch jobs to ensure efficient and accurate data loading.
• • A key collaborative element of this position is partnering with product and analytics teams. You will translate complex modeled data into Business Intelligence (BI)-ready views and provide guidance to dashboard teams on semantic layer design and the creation of consumption-optimized structures. Your expertise will directly enable enhanced data-driven insights and reporting.
• • You will ensure alignment of all data models with established data governance policies, standards, and business rules. Active participation in model reviews and change control forums is expected, contributing to a robust and well-governed data environment.
• • Facilitating clear and consistent daily communications and meetings will be essential. You will be expected to present findings and recommendations clearly and concisely to both technical and non-technical stakeholders, fostering understanding and buy-in for data initiatives.
• • This role requires a proactive and collaborative individual who thrives in a dynamic environment, contributing to the delivery of reliable, consumable data assets that are the bedrock of our Advisory products and decisioning capabilities.