Data Engineer-Data Platforms-Google
Hakkōda, an IBM Company
Bengaluru, Karnataka, India2h agovia LinkedIn
This job at a glance
- Who can apply
- Freshers
- Must know
- ETLPythonGCPSparkHadoopAirflow
- Work
- On-site in Bengaluru
- Pay
- Not stated by the employer.
- Skill demand
- Python23%GCP4%of 26 similar fresher jobs posted in India this week
- Listed
- 4 Nov 2026 · still open
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About the Role
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.
Key Responsibilities
- 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.
- Build and maintain data engineering solutions utilizing Google Cloud Storage, BigTable, DataProc with Spark and Hadoop, and DataFlow with Apache Beam or Python.
- Schedule and manage the data platform using Google Cloud Scheduler and Cloud Composer (Airflow), ensuring efficient data pipeline operations.
- Develop and implement data migration solutions using Google services, ensuring seamless data transfer between systems.
- Design and optimize the data layer using Google services such as BigQuery, Big Table, and Cloud Spanner, ensuring efficient data storage and retrieval.
Requirements & Tech Stack
- Expertise in 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.
- Experience in 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.
- Proficiency working with Google Cloud Storage, BigTable, BigQuery DataProc with Spark and Hadoop, and Google DataFlow with Apache Beam or Python.
- Knowledge of scheduling and managing the data platform using Google Cloud Scheduler and Cloud Composer (Airflow).
- Experience working with data layer design using Google services such as BigQuery, Big Table, and Cloud Spanner.
- Exposure to utilizing open-source technologies like Apache Airflow, dbt, Spark/Python, or Spark/Scala.
- Experience working with Google services to develop and implement data migration solutions.
- Exposure to using Cloud Composer (Airflow) for scheduling and managing the data platform.
Qualifications
- Data Engineering
- Data Pipelines
- Data Platform
- Google BigQuery
- BigTable
- Cloud Storage
- Data Migration Design
- Hadoop
- Management
- Delivery
- Pipelines
- Python
- Scala
- Programming Language
- Scheduling
- Spark
- Google Cloud
- Data Storage
- Real-time Data
- Open Source
- Apache Beam
- Apache Airflow