Senior Specialist - Data Engineering

LTIMindtree is a global technology consulting and digital solutions company that enables enterprises across industries to reimagine business models, accelerate innovation, and maximize growth by harnessing digital technologies. As a digital transformation partner to more than 750 clients, LTIMindtree brings extensive domain and technology expertise to help drive superior competitive differentiation, customer experiences, and business outcomes in a converging world.
Powered by nearly 90,000 talented and entrepreneurial professionals across more than 30 countries, LTIMindtree — a Larsen & Toubro Group company — combines the industryacclaimed strengths of erstwhile Larsen and Toubro Infotech and Mindtree in solving the most complex business challenges and delivering transformation at scale.
Job Description:
The role involves working closely with the business in a consultative fashion, suggesting them on the best practice Snowflake set-up and represent the interests of the group in overall governance board,
• Design and implement Snowflake cloud data platform to support clients cloud data journey. Simultaneously align with the central teams around overall governance and interoperability
• Work with business to assess technical feasibility of the identified data products.
• Analyse identified use cases with respect to data needs.
• Contribute to architecture solution design - use case prioritization, Analyse gaps and define target solution, define a roadmap to onboards different data assets / data products.
• Configure Snowflake with foundation capabilities: RBAC controls, Data Ingestion Capabilities, Data Storage Capacities, Data pipeline in production, Enterprise security and governance, DataOps foundation.
• Scalable data foundation for business needs, providing reliable data for analysis needs with right level of granularity for analysis.
• Improve overall data quality and data governance by managing data assists in a structured manner.
• Enable data-as-a-service by sharing data products across organization stakeholders via various sharing mechanisms such as APIs etc.
• Unlock advanced analytics at scale, being able to use, build & deploy data products in the Mesh
• Tool selection for end-to-end data architecture, technical architecture design and implementation oversight
• Responsible for ensuring the data platform functions optimally, while meeting data needs of the stakeholders
• Source system onboarding as per the agreed roadmap
• Monitor data processes and routines and optimize their performance.