Data Platform Engineer

Summary

Experience:

• Overall IT experience (No of years) - 9+
• Data Modeling Experience - 5+
• Data Vault Modeling Experience - 3+

Key Responsibilities:

• Drive discussions with clients deal teams to understand business requirements, how Data Model fits in implementation and solutioning
• Develop the solution blueprint and scoping, estimation in delivery project and solutioning
• Drive Discovery activities and design workshops with client and lead strategic road mapping and operating model design discussions
• Design and develop Data Vault 2.0-compliant models, including Hubs, Links, and Satellites.
• Design and develop Raw Data Vault and Business Data Vault.
• Translate business requirements into conceptual, logical, and physical data models.
• Work with source system analysts to understand data structures and lineage.
• Ensure conformance to data modeling standards and best practices.
• Collaborate with ETL/ELT developers to implement data models in a modern data warehouse environment (e.g., Snowflake, Databricks, Redshift, BigQuery).
• Optimize data architecture for performance, scalability, and reliability.
• Document models, data definitions, and metadata.
• Support data governance, quality, and master data management initiatives.
• Participate in code reviews, modeling workshops, and agile ceremonies (if applicable).

Technical Experience:

• 9+ year overall IT experience, 5+ years in Data Modeling and 3+ years in Data Vault Modeling
• Design and development of Raw Data Vault and Business Data Vault.
• Strong understanding of Data Vault 2.0 methodology, including business keys, record tracking, and historical tracking.
• Data modeling experience in Dimensional Modeling/3-NF modeling
• Hands-on experience with any data modeling tools (e.g., ER/Studio, ERwin, or similar).
• Hands-on experience in any Data Vault automation tool (e.g., Vault Speed, WhereScape, biGENIUS-X, dbt, or similar).
• Solid understanding of ETL/ELT processes, data integration, and warehousing concepts.
• Experience with any modern cloud data platforms (e.g., Snowflake, Databricks, Azure Synapse, AWS Redshift, or Google Big Query).
• Must be familiar with Data Architecture Principles.
• Excellent SQL skills.

Good to Have Skills:

• Any one of these add-on skills - Graph Database Modelling, RDF, Document DB Modeling, Ontology, Semantic Data Modeling
• Preferred understanding of Data Analytics on Cloud landscape and Data Lake design knowledge.
• Cloud Data Engineering, Cloud Data Integration

Professional Experience:

• Strong requirement analysis and technical solutioning skill in Data and Analytics
• Excellent writing, communication and presentation skills.
• Eagerness to learn new skills and develop self on an ongoing basis.
• Good client facing and interpersonal skills
• Educational Qualification :

:

- B.E or B.Tech must

Qualification15 years full time education