Data Engineer-Data Platforms-SnowFlake

Role overview

Data Engineer-Data Platforms-SnowFlake at IBM

Responsibilities

• You’ll be encouraged to challenge the norm, explore new ideas, and create innovative solutions that deliver real results.
• Implement Data and AI usecases: Implement Data and AI usecases on Snowflake platforms, ensuring seamless integration and optimal performance.

Employment details

• India Software Engineering Hybrid Professional Bangalore, IN Bangalore (0063) IBM India Private Limited Architecture Artificial Intelligence Business Requirements Cloud Computing Data Modeling Data Warehousing Extract, Transform, Load Integration Optimization Reliability Scalability Security Encryption Data Engineering Snowflake Data Warehouse Cloud security Compliance Data Platform Complex Data Data Partitioning
• Location: Bangalore [India]

About the employer

• A career in IBM Consulting is built on long-term client relationships and close collaboration worldwide.
• With support from our strategic partners, robust IBM technology, and Red Hat, you’ll have the tools to drive meaningful change and accelerate client impact.

Additional role details

• You’ll work with leading companies across industries, helping them shape their hybrid cloud and AI journeys.
• At IBM Consulting, curiosity fuels success.
• Our culture of growth and empathy focuses on your long-term career development while valuing your unique skills and experiences.
• As a Data Engineer specializing in Data Platforms-SnowFlake, you will play a critical role in building and enhancing Snowflake platforms for client's Data and AI usecases.
• This role involves implementing Data and AI usecases on Snowflake platforms, requiring strong technical expertise and collaboration.
• Your primary responsibilities will include:
• Enhance Snowflake platform: Build and enhance Snowflake platform to meet client's Data and AI requirements, applying data engineering principles and best practices.
• Leverage Cloud capabilities: Utilize Cloud capabilities to support Snowflake platform development, ensuring scalability and reliability.
• Exposure to Snowflake platforms: Familiarity with Snowflake architecture, features, and best practices for implementing Data and AI usecases.
• Experience with Data Engineering: Knowledge of data engineering principles, including data modeling, data warehousing, and ETL processes.
• Cloud computing skills: Understanding of Cloud capabilities, including scalability, reliability, and security, to support Snowflake platform development.
• Data and AI usecase implementation: Experience with implementing Data and AI usecases on cloud-based platforms, ensuring seamless integration and optimal performance.
• Data platform development: Exposure to building and enhancing data platforms to meet business requirements, applying data engineering principles and best practices.
• Cloud Security Knowledge: Exposure to Cloud security features, including data encryption, access controls, and compliance, to ensure secure Snowflake platform development.
• Advanced Data Modeling: Experience with advanced data modeling techniques, including data warehousing and ETL processes, to support complex Data and AI usecases.
• Scalability Optimization: Understanding of scalability optimization techniques, including data partitioning and caching, to ensure high-performance Snowflake platform operation.