IBM Hiring Data Engineer (Hyderabad) | Hybrid Google Data Platforms Role

A career in IBM Consulting is built on long-term client relationships and close collaboration worldwide. You will work with leading companies across industries, helping them shape their hybrid cloud and AI journeys. Backed by strategic partners, IBM technology, and Red Hat, you will have the tools to drive meaningful change and speed up client impact.

At IBM Consulting, curiosity fuels success. You will be encouraged to question the norm, explore new ideas, and build 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 Bigtable.
• 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), keeping data pipeline operations efficient.
• 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, Bigtable, and Cloud Spanner, ensuring efficient data storage and retrieval.

Exposure and Experience

• Exposure to Google Cloud services including DataProc, DataFlow, PubSub, BigQuery, Bigtable, Cloud Spanner, CloudSQL, and AlloyDB.
• Experience developing and managing batch and real-time pipelines using open-source technologies such as Apache Airflow, dbt, Spark/Python, or Spark/Scala.
• Exposure to Cloud Composer (Airflow) for scheduling and managing the data platform.
• Experience with data layer design using BigQuery, Bigtable, and Cloud Spanner for efficient storage and retrieval.
• Experience using Google services to develop and implement data migration solutions.