IBM Data Engineer – Data Platforms (Google) Recruitment 2026 | Hybrid Job Opportunity in Bangalore
Are you an experienced Data Engineer looking for an
exciting opportunity to work with cutting-edge Google Cloud Platform (GCP)
technologies? IBM is hiring talented professionals for the position of Data
Engineer – Data Platforms (Google) in Bangalore, Karnataka, India.
This hybrid role offers the opportunity to work on enterprise-scale data
engineering projects, cloud data platforms, big data technologies, artificial
intelligence solutions, and modern analytics systems.
If you have experience in Google Cloud Platform,
BigQuery, Apache Spark, DataFlow, DataProc, Cloud Composer, Airflow, BigTable,
Cloud Spanner, Python, Hadoop, and Data Engineering, this could be an
excellent opportunity to advance your career with one of the world's leading
technology companies.
In this article, you'll find the complete job overview, responsibilities, required skills, qualifications, benefits, preparation tips, and the official company application link.
About IBM Careers
IBM is one of the world's most recognized technology
companies, helping organizations modernize their business through Artificial
Intelligence, Hybrid Cloud, Data Analytics, Automation, Cybersecurity, and
Consulting Services.
IBM Consulting works closely with enterprises worldwide to
deliver innovative digital transformation projects using cloud-native
technologies, AI-powered platforms, and scalable enterprise solutions.
Working at IBM gives professionals the opportunity to
collaborate with global clients while continuously learning the latest
technologies and industry best practices.
Job Overview
Job Title: Data Engineer – Data Platforms (Google)
Company: IBM India Private Limited
Job Location: Bangalore, Karnataka, India
Work Mode: Hybrid
Employment Type: Regular
Experience Required: 7–9 Years
Education Required: Bachelor's Degree
Preferred Qualification: Master's Degree
Department: Data & Analytics
Travel Requirement: Up to 20%
Shift: General (Day Shift)
Key Responsibilities
As a Google Cloud Data Engineer at IBM, you will play an
important role in building highly scalable enterprise data platforms.
Your responsibilities include:
- Design
enterprise Data Lake and Data Warehouse architectures.
- Develop
batch and real-time data pipelines.
- Build
cloud-native data engineering solutions using Google Cloud.
- Create
scalable ETL and ELT workflows.
- Work
with Google Cloud Storage for large-scale datasets.
- Develop
pipelines using Apache Beam, Spark, Python, and Hadoop.
- Build
streaming solutions using Pub/Sub.
- Manage
workflows using Cloud Composer (Airflow).
- Schedule
jobs through Google Cloud Scheduler.
- Design
optimized BigQuery data models.
- Work
with BigTable and Cloud Spanner databases.
- Perform
enterprise data migration projects.
- Improve
data quality, scalability, and performance.
- Collaborate
with cloud architects, business analysts, and development teams.
- Support
enterprise analytics and AI initiatives.
Required Technical Skills
IBM is looking for professionals with strong knowledge in
modern cloud data engineering technologies.
Preferred technical skills include:
- Google
Cloud Platform (GCP)
- BigQuery
- Google
Cloud Storage
- DataFlow
- DataProc
- Pub/Sub
- BigTable
- Cloud
Spanner
- Cloud
SQL
- AlloyDB
- Apache
Spark
- Hadoop
- Apache
Beam
- Apache
Airflow
- Cloud
Composer
- dbt
- Python
- Spark
Scala
- ETL
Development
- ELT
Pipelines
- Data
Warehouse
- Data
Lake
- Real-Time
Data Processing
- Batch
Processing
- Data
Migration
- Data
Modeling
- Cloud
Data Engineering
Educational Qualification
Applicants should possess:
- Bachelor's
Degree (Required)
- Master's
Degree (Preferred)
Candidates with strong cloud certifications and practical
Google Cloud experience will have an added advantage.
Experience Required
IBM is seeking professionals with:
- 7–9
years of Data Engineering experience
- Experience
working on enterprise cloud migration projects
- Knowledge
of scalable analytics platforms
- Experience
building production-ready cloud data pipelines
Why Join IBM?
IBM offers one of the best environments for technology
professionals who want to build long-term careers.
Some advantages include:
- Hybrid
work environment
- Global
enterprise projects
- Career
growth opportunities
- AI-driven
innovation
- Hybrid
Cloud technologies
- Continuous
learning programs
- International
client exposure
- Collaborative
work culture
- Industry-leading
consulting projects
- Competitive
employee benefits
Professionals working at IBM gain valuable experience
working with Fortune 500 organizations across multiple industries.
Who Should Apply?
This opportunity is ideal for professionals working as:
- Data
Engineer
- Google
Cloud Engineer
- Big
Data Engineer
- Cloud
Data Engineer
- GCP
Developer
- ETL
Developer
- Analytics
Engineer
- BigQuery
Developer
- Data
Platform Engineer
- Data
Warehouse Engineer
- Data
Pipeline Engineer
- Cloud
Analytics Engineer
Essential Technologies You Should Know
To succeed in this role, candidates should be comfortable
working with:
- Google
Cloud Platform
- BigQuery
- DataFlow
- DataProc
- Apache
Spark
- Apache
Beam
- Airflow
- Cloud
Composer
- BigTable
- Cloud
Spanner
- Cloud
SQL
- Pub/Sub
- Hadoop
- Python
- dbt
- Data
Warehousing
- Data
Lakes
- Cloud
Migration
- Enterprise
Analytics
- Artificial
Intelligence Platforms
Career Growth Opportunities
This IBM role can open doors to higher-level positions such
as:
- Senior
Data Engineer
- Lead
Data Engineer
- Cloud
Data Architect
- GCP
Solutions Architect
- Analytics
Architect
- Principal
Data Engineer
- AI
Platform Engineer
- Data
Engineering Manager
- Cloud
Solution Consultant
Professionals experienced in Google Cloud Data Engineering
remain among the highest-paid technology specialists across global
organizations.
High-Value SEO Keywords
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- IBM
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- IBM
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How to Prepare and Practice After Applying
Submitting your application is only the first step. Many
candidates are shortlisted based on technical interviews, coding assessments,
cloud knowledge, and practical problem-solving skills. Preparing consistently
after applying can significantly improve your chances of success.
Focus on strengthening your understanding of Google Cloud
Platform services, especially BigQuery, DataFlow, DataProc, Cloud Storage,
Pub/Sub, BigTable, and Cloud Spanner. Practice building ETL and ELT pipelines
using Python, Apache Spark, Apache Beam, and Airflow. Review concepts related
to data warehouses, data lakes, partitioning, clustering, query optimization,
and distributed data processing.
Refresh your SQL skills by solving complex joins, window
functions, aggregations, and performance optimization problems. If possible,
create small cloud-based projects that demonstrate data ingestion,
transformation, orchestration, and reporting workflows. These hands-on projects
can be valuable discussion points during interviews.
Prepare for coding questions in Python, data engineering
scenarios, cloud architecture discussions, and behavioral interview questions
using the STAR (Situation, Task, Action, Result) method. Also, revisit core
concepts such as data modeling, batch processing, streaming pipelines,
scalability, fault tolerance, and monitoring.
Mock interviews with peers, practicing system design
questions, and reviewing IBM's values around innovation, collaboration, and
client success will help you feel more confident. Staying updated on Google
Cloud's latest features and industry best practices can also give you an
advantage during technical discussions.
Final Thoughts
The IBM Data Engineer – Data Platforms (Google) position
is an excellent opportunity for experienced cloud and data engineering
professionals who want to work on enterprise-scale Google Cloud projects. With
exposure to modern cloud technologies, AI-driven solutions, and global
consulting engagements, this role offers strong career growth, continuous
learning, and the chance to build impactful data platforms for leading
organizations.
Apply on the official company website: https://careers.ibm.com/en_US/careers/JobDetail?jobId=109875&source=WEB_Search_INDIA
