Data Engineer-Data Platforms-Google

IBM; Ernakulam; On-site; INR 1,500,000 - 2,800,000; Full time

Job summary

IBM Consulting India seeks a Data Engineer specializing in Google's data platforms to design, build and maintain data pipelines, migration, and data layer design.

You will leverage DataProc, DataFlow, Pub/Sub, BigQuery, BigTable, Cloud Spanner, and integrate with Apache Airflow, dbt, Spark/Python to deliver scalable solutions.

Join a team that values growth, curiosity, and collaboration across industries, delivering hybrid cloud and AI journeys for clients.

Qualifications

• Experience designing and building data pipelines for batch and real-time workloads.
• Proficiency with Google Cloud services like DataProc, DataFlow, Pub/Sub, BigQuery, BigTable, Cloud Spanner, and Cloud SQL.
• Strong knowledge of data platform management and data layer design.
• Experience with open source tooling such as Airflow, dbt, Spark/Python, or Spark/Scala.
• Master's degree preferred in a related field.

Responsibilities

• Design, build, and maintain data pipelines on Google Cloud for data warehouse and data lake.
• Implement data migration and ensure reliable data transfer between systems.
• Schedule and monitor data pipelines using Cloud Composer and Cloud Scheduler.
• Optimize data storage and retrieval with BigQuery, BigTable, and Cloud Spanner.
• Collaborate with teams to deliver data engineering solutions.

Skills

Google Cloud

Data pipelines

Open source

Cloud Composer

Data layer design

Python

Spark/Scala

Education

Master's degree

Tools

Apache Airflow

dbt

Spark

Python

Apache Beam

BigQuery

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 such as 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.