Data Architect

LTIMindtree is proud to be an equal opportunity employer. We are committed to equal employment opportunity regardless of race, ethnicity, nationality, gender, gender-identity, gender expression, language, age, sexual orientation, religion, marital status, veteran status, socio-economic status, disability or any other characteristic protected by applicable law.

We are Hiring for Data Architect !!

Experience: 12 to 17 years

Working Days – Sunday to Thursday

Please share your updated resume –

Job Description:

Primarily skills - Mainly Azure Data Architect / Data Warehousing + Data Modelling.

Support Lead Data Architect in data ingestion, integration, transformation, and modeling activities.

Develop and maintain Conceptual Data Models (CDM), Logical Data Models (LDM), and Physical Data Models (PDM) using ERWIN, Create, update & Review Data Dictionaries.

Ensure data modeling practices align with NOC standards and enterprise architecture guidelines.

Create, review, and update Integration Design Documents (IDD), Low-Level Design (LLD), and High-Level Design (HLD).

Assist in Master Data Management (MDM) initiatives using Informatica IDMC, ensuring consistency and accuracy of master data.

Support Data Governance toolsets including data lineage tracking, data dictionaries, and metadata management.

Collaborate with DataOps, Data Engineering, and Data Analysts to ensure data quality and operational efficiency.

Participate in Architecture Review Board (ARB) sessions to review and validate data architecture solutions when required along with Design Advisory.

Ensure integration of Information Security best practices in all data architecture processes.

Work with Azure Data Lake, Azure Synapse, Azure SQL Databases, Azure Event Hub, Azure Stream Analytics, and MS Fabric as well as Informatica Stack (IDMC and on Prem DG& MDM)

Design and optimize lakehouse and warehouse architecture for scalable data storage and analytics.

Develop dimensional and semantic data models to support business intelligence and reporting.

Leverage Copilot and Data Agent technologies to enhance automation and monitoring of data architecture workflows.

Participate in weekly meetings and design reviews to share updates and contribute to continuous improvement.

Make sure DM Requirements for data related project are shared with key stakeholders at the start of the project.

Regards,

Aditya Utekar

LTIMindtree