IBM Hiring Data Engineer, Google Data Platforms (Bangalore) | Hybrid

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 strategic partners, 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. The 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 Google's data platforms, you will design, build, and maintain data engineering solutions on Google's Cloud ecosystem. The role calls for expertise in using various Google services for batch and real-time data pipelines, data migration, and data layer design.

Key Responsibilities

• Design Data Pipelines: Design and develop batch and real-time data pipelines for Data Warehouse and Datalake using Google services such as DataProc, DataFlow, PubSub, BigQuery, and Big Table.
• Develop Data Engineering Solutions: Use Google Cloud Storage, BigTable, BigQuery, DataProc with Spark and Hadoop, and Google DataFlow with Apache Beam or Python to build and maintain data engineering solutions.
• Manage Data Platforms: Schedule and manage the data platform using Google Cloud Scheduler and Cloud Composer (Airflow), ensuring efficient pipeline operations.
• Implement Data Migration: Develop and implement data migration solutions using Google services, ensuring seamless data transfer between systems.
• Optimize Data Layer: Design and optimize the data layer using BigQuery, Big Table, and Cloud Spanner, ensuring efficient data storage and retrieval.

Preferred Experience

• Exposure to designing, building, and maintaining data engineering solutions on Google's Cloud ecosystem, including DataProc, DataFlow, PubSub, BigQuery, Big Table, Cloud Spanner, CloudSQL, and AlloyDB.
• Exposure to developing and managing batch and real-time data pipelines using Google services and open-source technologies like Apache Airflow, dbt, Spark/Python, or Spark/Scala.
• Experience working with Google Cloud Storage, BigTable, BigQuery, DataProc with Spark and Hadoop, and Google DataFlow with Apache Beam or Python.
• Exposure to scheduling and managing the data platform with Google Cloud Scheduler and Cloud Composer (Airflow).
• Experience with data layer design using BigQuery, Big Table, and Cloud Spanner for efficient storage and retrieval.
• Experience developing data migration solutions with Google services to ensure seamless data transfer between systems.