Data Engineer-Data Platforms-Google

IBM; Hyderabad; On-site; INR 1,200,000 - 1,900,000; Full time

Job summary

IBM Consulting seeks a Data Engineer to design and maintain data pipelines on Google Cloud. You will architect batch and real-time flows, leveraging DataProc, DataFlow, Pub/Sub, BigQuery, and BigTable to empower data-driven decisions across client environments.

You will implement data migration strategies, manage scheduling with Cloud Composer, and optimize the data layer using BigQuery, BigTable, and Cloud Spanner for scalable, reliable performance.

Qualifications

• Experience designing, building, and maintaining data engineering solutions on Google Cloud.
• Experience developing batch and real-time data pipelines for Data Warehouse and Datalake.
• Proficiency with Google Cloud services and data layer design.
• Familiarity with scheduling data platforms using Airflow/Cloud Composer.
• Understanding of data migration and scalable storage solutions.

Responsibilities

• Design and develop batch and real-time data pipelines using Google services (DataProc, DataFlow, Pub/Sub, BigQuery, BigTable).
• Build data engineering solutions using Google Cloud Storage, BigTable, BigQuery/DataProc with Spark/Hadoop.
• Manage data platforms with Cloud Scheduler and Cloud Composer for reliable pipelines.
• Implement data migration solutions across systems with Google services.
• Design and optimize data layer using BigQuery, BigTable, Cloud Spanner.

Skills

Google Cloud Ecosystem

Data Pipeline Development

Google Cloud Services

Data Platform Management

Data Layer Design

Education

Master's Degree

Tools

Apache Airflow

dbt

Spark/Python

Spark/Scala

Terraform

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 Google's data platforms, you will design, build, and maintain data engineering solutions on Google's Cloud ecosystem. This role requires expertise in utilizing various Google services for batch and real-time data pipelines, data migration, and data layer design. Your primary responsibilities will include:

• 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: Utilize 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 data 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 Google services such as BigQuery, Big Table, and Cloud Spanner, ensuring efficient data storage and retrieval.

Preferred Education

Master's Degree

Required Technical And Professional Expertise

• Google Cloud Ecosystem Expertise: Exposure to designing, building, and maintaining data engineering solutions on Google's Cloud ecosystem, including services such as Google DataProc, DataFlow, PubSub, BigQuery, Big Table, Cloud Spanner, CloudSQL, and AlloyDB.
• Data Pipeline Development Experience: Exposure to developing and managing batch and real-time data pipelines for Data Warehouse and Datalake using Google services and open-source technologies like Apache Airflow, dbt, Spark/Python, or Spark/Scala.
• Google Cloud Services Proficiency: Experience working with 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.
• Data Platform Management Knowledge: Exposure to scheduling and managing the data platform using Google Cloud Scheduler and Cloud Composer (Airflow) for efficient data pipeline operations.
• Data Layer Design Understanding: Experience working with data layer design using Google services such as BigQuery, Big Table, and Cloud Spanner for efficient data storage and retrieval.

Preferred Technical And Professional Experience

• Open Source Technologies: Exposure to utilizing open-source technologies like Apache Airflow, dbt, Spark/Python, or Spark/Scala for developing and managing batch and real-time data pipelines.
• Data Migration Solutions: Experience working with Google services to develop and implement data migration solutions, ensuring seamless data transfer between systems.
• Cloud Composer Expertise: Exposure to using Cloud Composer (Airflow) for scheduling and managing the data platform, ensuring efficient data pipeline operations, Good to have : Git, Terraform and Python API implementation.