Data Engineer-Data Platforms-Google

codingcircle; Bengaluru; Hybrid; INR 600,000 - 900,000; Full time

Job summary

IBM India Private Limited seeks a Data Engineer specializing in Google’s data platforms to design and maintain data engineering solutions. The entry-level position offers a hybrid work arrangement in Bengaluru. Responsibilities include developing data pipelines, utilizing Google services, and managing data platforms. Candidates should have a Bachelor's Degree and proficiency in the Google Cloud ecosystem. Experience with tools like Apache Airflow and BigQuery is preferred.

Qualifications

• Expertise in designing, building, and maintaining data engineering solutions on Google Cloud.
• Experience in developing and managing batch and real-time data pipelines.
• Proficient in using Google services like BigTable and Cloud Spanner for data layer design.

Responsibilities

• Design and develop data pipelines using Google Cloud services.
• Utilize Google Cloud Storage and BigQuery for data engineering solutions.
• Manage the data platform operations with Google Cloud Scheduler.

Skills

Google Cloud Services Proficiency

Data Pipeline Development Experience

Google Cloud Ecosystem Expertise

Data Platform Management Knowledge

Data Layer Design Understanding

Education

Bachelor’s Degree

Tools

Apache Airflow

BigQuery

Google DataProc

Google DataFlow

Python

Job description

IBM India Private Limited Bangalore Full-time Fresher Not Disclosed Posted 2 days ago

Company :- IBM India Private Limited
Job Title :- Data Engineer-Data Platforms-Google
Job ID :- 85936
City / Township / Village :- Bangalore
State / Province :- Karnataka
Country :- India
Work arrangement :- Hybrid
Area of work :- Data & Analytics
Employment Type :- Regular
Position type :- Entry Level
Travel required :- Up to 20% or 1 day a week
Shift :- General (daytime)
Is this role a commissionable/sales incentive based position? :- No
Years of Experience :- 0–7

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.

In this role, you’ll work in one of our IBM Consulting Client Innovation Centers (Delivery Centers), where we deliver deep technical and industry expertise to a wide range of public and private sector clients around the world. Our delivery centers offer our clients locally based skills and technical expertise to drive innovation and adoption of new technology.

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.

Required education

Bachelor’s Degree

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.