Data Modeler & Data Lineage Analyst

LIC Housing Finance Limited; Mumbai; On-site; INR 900,000 - 1,300,000; Full time

Job summary

LIC Housing Finance Limited in Mumbai seeks a Data Modeler & Data Lineage Analyst to support the ISDMA platform, focusing on enterprise data modelling, data lineage, metadata management, and data standardization across the Data Lakehouse ecosystem.

The role requires 3+ years of experience and an MCA/BE/BTech/BSc in CS/IT/Data Science with at least 60%. BFSI exposure is preferred; strong SQL, governance knowledge, and stakeholder collaboration are essential.

Qualifications

• Education: Full-Time MCA, B.E./B.Tech/B.Sc. in CS/IT/DS with minimum 60% from a recognized university.
• Experience: 3+ years in relevant field (HFC/BFSI/NBFC preferred).
• Role: Support ISDMA data management, modelling, lineage, metadata and standardization across Data Lakehouse; exposure to governance will help.

Responsibilities

• Design and maintain enterprise data models (conceptual, logical, physical).
• Map data lineage across source, transformation and target layers.
• Manage metadata, data dictionaries, and business glossaries.
• Coordinate with Data Architects, Engineers, and BI teams on data requirements and governance.
• Support data integration/ETL processes and data quality controls.
• Assist in data governance implementation, ownership, stewardship, and compliance.
• Document data models, lineage, and governance activities; enable impact analysis.

Skills

Data Modelling

Data Lineage

SQL

Data Governance

Metadata Management

Data Quality

Documentation

Stakeholder Management

Education

MCA/B.E./B.Tech/B.Sc. in CS/IT/Data Science (60%)

Tools

Collibra

Informatica

Microsoft Purview

IBM Knowledge Catalog

Alation/Atlan/erwin

Job description

• Position Title: Data Modeler & Data Lineage Analyst
• Department/Vertical: IT
• 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 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
• Metadata Management

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.
• 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.
• 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.