Data Platform Engineer

Project Role : Data Platform Engineer

Project Role Description : Assists with the data platform blueprint and design, encompassing the relevant data platform components. Collaborates with the Integration Architects and Data Architects to ensure cohesive integration between systems and data models.

Must have skills : Data Modeling Techniques and Methodologies

Good to have skills : NA

Minimum 7.5 Year(s) Of Experience Is Required

Educational Qualification : 15 years full time education

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:

Good to Have Skills:

• 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