Data Engineer-Data Platforms-SnowFlake

IBM; Bengaluru; On-site; INR 1,800,000 - 2,800,000; Full time

Job summary

IBM Bengaluru is seeking a Data Engineer specializing in Snowflake data platforms to design and optimize data pipelines for client usecases in Data and AI.

You will implement Data and AI usecases on Snowflake platforms, enhance the Snowflake platform to meet business requirements, and leverage cloud capabilities to deliver scalable, secure, and reliable data solutions across client environments.

Qualifications

• Experience with Snowflake platforms and architectures.
• Strong knowledge of data modeling, warehousing, and ETL.
• Understanding of cloud capabilities and security considerations.
• Experience implementing Data and AI usecases on cloud platforms.
• Experience building and enhancing data platforms.

Responsibilities

• Implement Data and AI usecases on Snowflake platforms to ensure seamless integration and performance.
• Enhance Snowflake platform to meet client Data and AI requirements using data engineering best practices.
• Leverage cloud capabilities to support Snowflake platform development with scalability and reliability.

Skills

Snowflake familiarity

Data engineering

Cloud computing

Data & AI usecase implement

Data platform development

Education

Master's Degree

Tools

Snowflake

Job description

Introduction

A career in IBM Consulting is built on long-term client relationships and close collaboration worldwide. You'll work with leading companies across industries, helping them shape their hybrid cloud and AI journeys. 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. At IBM Consulting, curiosity fuels success. You'll be encouraged to challenge the norm, explore new ideas, and create innovative solutions that deliver real results. Our culture of growth and empathy focuses on your long-term career development while valuing your unique skills and experiences.

Your Role And Responsibilities

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:

• Implement Data and AI usecases: Implement Data and AI usecases on Snowflake platforms, ensuring seamless integration and optimal performance.
• 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.

Preferred Education

Master's Degree

Required Technical And Professional Expertise

• 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.

Preferred Technical And Professional Experience

• 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.