Sr. Analyst-DA&A – Senior Data Architect / Data Modeler

6 to 9 Years of relevant experience in Data Architecture, Data Modeling, and Cloud Data Warehousing.

India

We are seeking an experienced Senior Data Architect / Data Modeler to design, develop, and maintain enterprise-scale data models and modern cloud-based data warehouse solutions for the Sr. Analyst-DA&A role.
The ideal candidate should have strong expertise in dimensional and relational data modeling, cloud data platforms, data architecture, and data warehousing, with the ability to collaborate closely with business and technical stakeholders.
Candidate must have relevant experience of 6-9 Years.

• Design conceptual, logical, and physical data models for enterprise applications.
• Gather and analyze business requirements with stakeholders, business analysts, and SMEs.
• Develop scalable and high-performance data warehouse architectures.
• Design and implement data models for OLTP, OLAP, and hybrid environments.
• Lead cloud migration initiatives involving enterprise data platforms.
• Build and optimize data solutions using Snowflake, Amazon Redshift, SQL Server, or Teradata.
• Develop and maintain database objects including SQL queries, views, stored procedures, and functions.
• Collaborate with data engineering teams to ensure data consistency, integrity, and governance.
• Create and maintain data dictionaries, metadata, and technical documentation.
• Support ETL/ELT design, data integration, and transformation processes.
• Participate in Agile/Scrum ceremonies and work closely with cross-functional teams.
• Mentor junior team members and review data models for quality and best practices.
• Apply Data Automation & AI principles to improve data engineering and analytics workflows.
• Work on Data Engineering - Data Analytics - DataBricks (Technical) to build and optimize data pipelines and analytical solutions.
• Ensure alignment of data models and solutions with enterprise data strategy and governance standards.

• Strong expertise in Data Modeling (Conceptual, Logical, Physical).
• Experience with Erwin Data Modeler.
• Hands-on experience with Snowflake, Amazon Redshift, Teradata, and SQL Server / T-SQL.
• Proficiency in SQL Programming and dbt.
• Experience working on AWS Cloud-based data solutions.
• Strong understanding of Data Warehousing and ETL/ELT concepts.
• Knowledge of Data Architecture, Dimensional Modeling (Kimball), and Inmon Data Warehouse Architecture.
• Experience in Database Performance Optimization.
• Familiarity with Git/GitHub for version control.
• Understanding of Data Governance concepts.
• Experience working in Agile/Scrum methodologies.
• Exposure to Data Automation & AI-based solutions in data engineering and analytics.
• Ability to collaborate in a multi-disciplinary DA&A environment and support complex analytical use cases.

• Bachelor’s degree in Computer Science, Information Technology, or related discipline.
• Strong expertise in Data Modeling (Conceptual, Logical, Physical) and Enterprise Data Modeling.
• Experience with Erwin Data Modeler.
• Proficiency in Snowflake, Amazon Redshift, Teradata, and SQL Server / T-SQL.
• Strong SQL Programming skills and experience with dbt.
• Hands-on experience with AWS Cloud and Data Warehousing.
• Strong understanding of ETL/ELT concepts and Data Architecture.
• Experience with Dimensional Modeling (Kimball) and Inmon Data Warehouse Architecture.
• Experience in Database Performance Optimization.
• Familiarity with Git/GitHub and Data Governance concepts.
• Experience working with Agile/Scrum methodologies.
• Professional Scrum Master (PSM) certification is an advantage.
• Experience leading technical teams and mentoring engineers.
• Excellent communication and stakeholder management skills.
• Preferred domain experience in Healthcare, Financial Services, Retail / Consumer Goods, or Education.
• Key competencies include Data Architecture, Enterprise Data Modeling, Cloud Data Platforms, Solution Design, Requirement Analysis, Problem Solving, Leadership, Stakeholder Management, Technical Documentation, and Agile Delivery.
• Experience with DataBricks (Technical) for Data Engineering and Analytics.
• Good to have skills: Azure Databricks, Microsoft Fabric, Azure SQL Database, Python, Collibra, Informatica PowerCenter, S3, and Unix Shell Scripting.