Data Modeler & Data Lineage Analyst

1. Basic Position Details

• Position Title: Data Modeler & Data Lineage Analyst
• Department/Vertical: IT
• Location: Mumbai
• Reporting To (Designation): Deputy General Manager

2. Candidate Profile Requirements

A. Mandatory Criteria

• Education Qualification: Full-Time MCA, B.E. / B.Tech / B.Sc. in Computer Science / Information Technology / Data Science, or related discipline with minimum 60% aggregate from a recognized university. Distance Learning and Correspondence degrees will not be considered.
• Minimum % Required: 60%
• Minimum Experience Required: 3+ years
• Relevant Industry/Domain Experience: HFC / BFSI / NBFC (preferred)
• Role Overview: The incumbent will support the implementation, governance, and ongoing management of LIC HFL's enterprise-wide Integrated Solution for Data Management and Analytics (ISDMA) platform. The role will primarily focus on enterprise data modelling, data lineage management, metadata management, and data standardization across the Data Lakehouse ecosystem. Exposure to Data Governance frameworks and practices will be an added advantage.

B. Preferred Criteria

• Strong understanding of Data Modelling concepts and methodologies, including Conceptual, Logical, and Physical Data Models, dimensional modelling, and data modelling standards.
• Hands-on experience in Data Lineage mapping, metadata management, data discovery, and documentation across source, transformation, and target data layers.
• Good understanding of Enterprise Data Management, Data Warehousing, Data Lakehouse architectures, and modern data platforms.
• Strong proficiency in SQL and relational database concepts, including data structures, relationships, constraints, and query analysis.
• Practical understanding of Data Integration and ETL/ELT processes, including source-to-target mapping, transformation logic, data validation, and reconciliation.
• Familiarity with Enterprise Metadata Management, Data Cataloguing, Data Dictionary, Business Glossary, and Data Lineage tools.
• Exposure to Data Governance frameworks and industry best practices, including data ownership, stewardship, data quality, metadata standards, and governance processes.
• Experience working with Data Governance, Data Catalog, Metadata Management, Data Lineage, or Data Quality tools such as Collibra, Informatica, Microsoft Purview, IBM Knowledge Catalog, Alation, Atlan, erwin, or equivalent platforms.
• Understanding of data security, privacy, regulatory and compliance requirements applicable to financial institutions, including data classification, access controls, masking, encryption, retention, and auditability.
• Exposure to cloud-based data platforms, modern analytics architectures, and cloud/hybrid data management environments.
• Strong analytical, problem-solving, documentation, communication, and stakeholder management skills, with the ability to work effectively with business, technology, data governance, and vendor teams.
• Relevant professional certifications in Data Management, Data Modelling, Data Governance, Metadata Management, Data Engineering, or Cloud Data Platforms (e.g., DAMA CDMP, Databricks, Azure, AWS, or equivalent) will be an added advantage.

• Certifications (if any):

Relevant Certification from a recognized professional body/institution/vendor, such as DAMA International (CDMP), EDM Council (DCAM/CDMC), Collibra, Informatica, Microsoft, Databricks, Snowflake, AWS, Google Cloud or equivalent will be preferred in

• Data Management
• Data Governance
• Data Modelling
• Metadata Management
• Data Lineage
• Data Architecture or
• Data Engineering
• Languages Required: English; Hindi

3. Interview & Selection Process

• Any Skill Test / Assessments Needed: Yes
• Interview (Online / In-person): In Person

Desired Attributes

• Strong attention to detail and data accuracy.
• Ability to work across business and technology teams.
• Good communication and documentation skills.
• Ability to manage multiple priorities in a fast-paced project environment.

4. Roles & Responsibilities

Data Modelling

• Design, develop, and maintain conceptual, logical, and physical data models for enterprise data domains.
• Collaborate with business and technical stakeholders to understand data requirements and translate them into scalable data models.
• Define and maintain data structures, relationships, hierarchies, and business rules across the Data Lakehouse platform.
• Ensure adherence to enterprise data modelling standards and best practices.

Data Lineage & Metadata Management

• Document and maintain end-to-end data lineage from source systems through ingestion, transformation, storage, and reporting layers.
• Identify and map data flows across applications, databases, ETL pipelines, and analytics platforms.
• Maintain metadata repositories, data dictionaries, and business glossaries.
• Support impact analysis for changes in source systems, data models, and reporting requirements.

Data Quality & Standardization

• Assist in defining data standards, naming conventions, and data quality controls.
• Support identification and resolution of data inconsistencies and lineage gaps.
• Coordinate with ETL, Data Engineering, and BI teams to ensure consistency of data definitions and transformations.

Data Governance Support

• Support implementation of data governance processes, policies, and standards.
• Assist in maintaining data ownership, stewardship, and classification frameworks.
• Contribute to data cataloguing, metadata governance, and regulatory compliance initiatives.
• Support audit and compliance requirements relating to enterprise data management.

Stakeholder Coordination

• Work closely with Data Architects, Data Engineers, BI teams, business users, and implementation partners.
• Participate in data design reviews, requirement discussions, and project governance meetings.
• Prepare documentation and reports related to data models, lineage, metadata, and governance activities.