Elsevier
Senior Data Discovery and Enrichment Expert II
🇮🇳
Bengaluru, Karnataka
🕑
Full-Time
💰
TBD
💻
Data Science
🗓️
January 20th, 2026
CI/CD
DBT
PostgreSQL
Edtech.com's Summary
Elsevier is hiring a Senior Data Discovery and Enrichment Expert II. The role involves designing, documenting, and maintaining logical and physical data models for analytical and operational systems while collaborating with data architects, system owners, engineers, and business stakeholders to ensure robust data structures that support integrations, analytics, and reporting.
Highlights
- Translate business requirements and source-system structures into data models and source-to-target mappings
- Design dimensional, normalized, and Data Vault data models for the data platform
- Collaborate with Data Architect to align models with enterprise data strategy and standards
- Profile source data, identify quality issues, and propose design changes or remediation
- Produce and maintain documentation including ER diagrams, data dictionaries, and data lineage
- Support change management, schema migrations, versioning, and data governance activities
- Assist data engineers with model implementation, performance tuning, and testing
- Define data quality rules and implement validation frameworks and tests
- Strong proficiency in SQL, Python scripting, cloud data platforms (Snowflake), databases (PostgreSQL or equivalent), transformation tools (dbt), git, and data modeling tools (SqlDBM, Erwin)
- Preferred experience with metadata management and data lineage tools (e.g., Collibra) and Agile delivery environment
Senior Data Discovery and Enrichment Expert II Full Description
Senior Data Discovery and Enrichment Expert II
Data Modeller
Love working with data? Ready to create the data models that convert complex sources into scalable, trusted datasets that drive business decisions?
About our Team
Data is a huge part of our business, both within our product offerings, and in helping us to make business decisions. Our team collects, consolidates, and links data about the Elsevier Technology Landscape—its configuration and operational state—to support operational systems, analytics and reporting.
About the Role
We are looking for an experienced Data Modeller to join our Data Engineering team. You will design, document and maintain logical and physical data models for analytical and operational systems, working closely with the data architect, system owners, engineers, and business stakeholders. Your work will ensure robust, well-governed data structures that support system integrations, analytics and reporting.
Responsibilities
- Translate business requirements and source-system structures into clear data models and source-to-target mappings
- Design and maintain logical and physical data models for our data platform. Design may require dimensional models, normalized schemas and/or Data Vault models as appropriate for the use case
- Collaborate with the Data Architect to align models with enterprise data strategy, standards and architecture patterns
- Work with system owners and engineers to profile source data, identify data quality issues and propose design changes or remediation
- Produce and maintain model documentation, entity relationship diagrams (ERDs), data dictionaries, and data lineage
- Support change management: assess impacts of schema changes, coordinate migrations and versioning with engineering and release teams
- Contribute to data governance: participate in metadata management, stewardship, and model review boards
- Support data engineers in implementing models (DDL, transformations, dbt models, etc.) and in performance tuning and testing
- Assist in data quality rules definition and implement validation frameworks and tests
- Provide guidance to business stakeholders and junior team members on model interpretation and best practices
Requirements
- Previous experience in data modelling or data architecture roles
- Strong SQL skills; experience writing complex queries and working with large datasets.
- Proven experience creating logical and physical data models and ER diagrams.
- Familiarity with dimensional modelling (Kimball), Data Vault, and normalized modelling approaches.
- Hands-on experience with a modern cloud data platform such as Snowflake and databases (PostgreSQL or equivalent).
- Experience with transformation tooling (dbt or equivalent) and CI/CD practices for data pipelines.
- Familiarity with modelling tools (e.g. SqlDBM, Erwin)
- Experience in using git
- Scripting skills using python
- Comfortable profiling data, identifying quality issues and specifying remediation.
- Strong collaboration and stakeholder management skills; able to translate business needs into technical designs
- Good documentation skills and attention to detail
Preferred / nice-to-have
- Knowledge of metadata management and data lineage tools (e.g. Collibra) is desirable.
- Experience working in an Agile delivery environment
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