GCP Data Engineer
Capgemini
GCP Data Engineer
Job Description
GCP Data Engineer
📋 Job Overview
The GCP Data Engineer role at Capgemini Invent involves building and optimizing data pipelines and scalable architectures on Google Cloud Platform to support advanced analytics and machine learning. The position requires collaboration with data scientists, analysts, and developers to deliver high-quality data solutions while ensuring data quality, governance, and security. This role is ideal for professionals with 7-10 years of experience in cloud data engineering, focusing on innovative transformation projects.
📍 Location: Bangalore
💼 Experience Level: Experienced Professionals
🏢 Business Unit: INVENT
🎯 Key Responsibilities
- Build and optimize data pipelines
- Design scalable data architectures
- Enable advanced analytics and machine learning workflows on Google Cloud Platform (GCP)
- Collaborate with data scientists, analysts, and application developers to deliver high-quality data solutions
- Ensure data quality, governance, and security across all pipelines and storage layers
- Implement data quality checks and monitoring, ensuring data accuracy and reliability
✅ Required Qualifications
- 7–10 years of experience as a Google Cloud data engineer
- Hands-on expertise in GCP Dataflow, BigQuery, Pub/Sub, Cloud Composer, and Cloud Storage
- Proficiency in Python, PySpark, and strong SQL skills including query optimization and performance tuning
- Experience with big data tools (Hadoop, Spark, Kafka)
- Experience with relational/NoSQL databases such as Microsoft SQL Server, MySQL, PostgreSQL, Oracle, Hadoop, Cassandra, MongoDB
- Strong analytic skills for structured, semi-structured, and unstructured datasets
- Familiarity with data warehousing, data lake concepts, and ETL processes
⭐ Preferred Qualifications
- Certifications in latest technologies such as Generative AI
🛠️ Required Skills
- GCP Dataflow
- BigQuery
- Pub/Sub
- Cloud Composer
- Cloud Storage
- Python
- PySpark
- SQL (query optimization and performance tuning)
- Hadoop
- Spark
- Kafka
- Microsoft SQL Server
- MySQL
- PostgreSQL
- Oracle
- Cassandra
- MongoDB
- Data warehousing
- Data lake concepts
- ETL processes
- Analytic skills for structured, semi-structured, and unstructured datasets
- Data quality checks and monitoring
- Data governance and security
🎁 Benefits & Perks
- Flexible work arrangements including remote work and flexible hours
- Environment to maintain healthy work-life balance
- Career growth programs and diverse professional opportunities
- Access to valuable certifications in latest technologies such as Generative AI
Locations
- Bangalore, India
Salary
Estimated Salary Rangemedium confidence
2,500,000 - 4,200,000 INR / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- GCP Dataflowintermediate
- BigQueryintermediate
- Pub/Subintermediate
- Cloud Composerintermediate
- Cloud Storageintermediate
- Pythonintermediate
- PySparkintermediate
- SQL (query optimization and performance tuning)intermediate
- Hadoopintermediate
- Sparkintermediate
- Kafkaintermediate
- Microsoft SQL Serverintermediate
- MySQLintermediate
- PostgreSQLintermediate
- Oracleintermediate
- Cassandraintermediate
- MongoDBintermediate
- Data warehousingintermediate
- Data lake conceptsintermediate
- ETL processesintermediate
- Analytic skills for structured, semi-structured, and unstructured datasetsintermediate
- Data quality checks and monitoringintermediate
- Data governance and securityintermediate
Required Qualifications
- 7–10 years of experience as a Google Cloud data engineer (experience)
- Hands-on expertise in GCP Dataflow, BigQuery, Pub/Sub, Cloud Composer, and Cloud Storage (experience)
- Proficiency in Python, PySpark, and strong SQL skills including query optimization and performance tuning (experience)
- Experience with big data tools (Hadoop, Spark, Kafka) (experience)
- Experience with relational/NoSQL databases such as Microsoft SQL Server, MySQL, PostgreSQL, Oracle, Hadoop, Cassandra, MongoDB (experience)
- Strong analytic skills for structured, semi-structured, and unstructured datasets (experience)
- Familiarity with data warehousing, data lake concepts, and ETL processes (experience)
Preferred Qualifications
- Certifications in latest technologies such as Generative AI (experience)
Responsibilities
- Build and optimize data pipelines
- Design scalable data architectures
- Enable advanced analytics and machine learning workflows on Google Cloud Platform (GCP)
- Collaborate with data scientists, analysts, and application developers to deliver high-quality data solutions
- Ensure data quality, governance, and security across all pipelines and storage layers
- Implement data quality checks and monitoring, ensuring data accuracy and reliability
Benefits
- general: Flexible work arrangements including remote work and flexible hours
- general: Environment to maintain healthy work-life balance
- general: Career growth programs and diverse professional opportunities
- general: Access to valuable certifications in latest technologies such as Generative AI
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Answer 10 quick questions to check your fit for GCP Data Engineer @ Capgemini.
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GCP Data Engineer
Capgemini
GCP Data Engineer
Job Description
GCP Data Engineer
📋 Job Overview
The GCP Data Engineer role at Capgemini Invent involves building and optimizing data pipelines and scalable architectures on Google Cloud Platform to support advanced analytics and machine learning. The position requires collaboration with data scientists, analysts, and developers to deliver high-quality data solutions while ensuring data quality, governance, and security. This role is ideal for professionals with 7-10 years of experience in cloud data engineering, focusing on innovative transformation projects.
📍 Location: Bangalore
💼 Experience Level: Experienced Professionals
🏢 Business Unit: INVENT
🎯 Key Responsibilities
- Build and optimize data pipelines
- Design scalable data architectures
- Enable advanced analytics and machine learning workflows on Google Cloud Platform (GCP)
- Collaborate with data scientists, analysts, and application developers to deliver high-quality data solutions
- Ensure data quality, governance, and security across all pipelines and storage layers
- Implement data quality checks and monitoring, ensuring data accuracy and reliability
✅ Required Qualifications
- 7–10 years of experience as a Google Cloud data engineer
- Hands-on expertise in GCP Dataflow, BigQuery, Pub/Sub, Cloud Composer, and Cloud Storage
- Proficiency in Python, PySpark, and strong SQL skills including query optimization and performance tuning
- Experience with big data tools (Hadoop, Spark, Kafka)
- Experience with relational/NoSQL databases such as Microsoft SQL Server, MySQL, PostgreSQL, Oracle, Hadoop, Cassandra, MongoDB
- Strong analytic skills for structured, semi-structured, and unstructured datasets
- Familiarity with data warehousing, data lake concepts, and ETL processes
⭐ Preferred Qualifications
- Certifications in latest technologies such as Generative AI
🛠️ Required Skills
- GCP Dataflow
- BigQuery
- Pub/Sub
- Cloud Composer
- Cloud Storage
- Python
- PySpark
- SQL (query optimization and performance tuning)
- Hadoop
- Spark
- Kafka
- Microsoft SQL Server
- MySQL
- PostgreSQL
- Oracle
- Cassandra
- MongoDB
- Data warehousing
- Data lake concepts
- ETL processes
- Analytic skills for structured, semi-structured, and unstructured datasets
- Data quality checks and monitoring
- Data governance and security
🎁 Benefits & Perks
- Flexible work arrangements including remote work and flexible hours
- Environment to maintain healthy work-life balance
- Career growth programs and diverse professional opportunities
- Access to valuable certifications in latest technologies such as Generative AI
Locations
- Bangalore, India
Salary
Estimated Salary Rangemedium confidence
2,500,000 - 4,200,000 INR / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- GCP Dataflowintermediate
- BigQueryintermediate
- Pub/Subintermediate
- Cloud Composerintermediate
- Cloud Storageintermediate
- Pythonintermediate
- PySparkintermediate
- SQL (query optimization and performance tuning)intermediate
- Hadoopintermediate
- Sparkintermediate
- Kafkaintermediate
- Microsoft SQL Serverintermediate
- MySQLintermediate
- PostgreSQLintermediate
- Oracleintermediate
- Cassandraintermediate
- MongoDBintermediate
- Data warehousingintermediate
- Data lake conceptsintermediate
- ETL processesintermediate
- Analytic skills for structured, semi-structured, and unstructured datasetsintermediate
- Data quality checks and monitoringintermediate
- Data governance and securityintermediate
Required Qualifications
- 7–10 years of experience as a Google Cloud data engineer (experience)
- Hands-on expertise in GCP Dataflow, BigQuery, Pub/Sub, Cloud Composer, and Cloud Storage (experience)
- Proficiency in Python, PySpark, and strong SQL skills including query optimization and performance tuning (experience)
- Experience with big data tools (Hadoop, Spark, Kafka) (experience)
- Experience with relational/NoSQL databases such as Microsoft SQL Server, MySQL, PostgreSQL, Oracle, Hadoop, Cassandra, MongoDB (experience)
- Strong analytic skills for structured, semi-structured, and unstructured datasets (experience)
- Familiarity with data warehousing, data lake concepts, and ETL processes (experience)
Preferred Qualifications
- Certifications in latest technologies such as Generative AI (experience)
Responsibilities
- Build and optimize data pipelines
- Design scalable data architectures
- Enable advanced analytics and machine learning workflows on Google Cloud Platform (GCP)
- Collaborate with data scientists, analysts, and application developers to deliver high-quality data solutions
- Ensure data quality, governance, and security across all pipelines and storage layers
- Implement data quality checks and monitoring, ensuring data accuracy and reliability
Benefits
- general: Flexible work arrangements including remote work and flexible hours
- general: Environment to maintain healthy work-life balance
- general: Career growth programs and diverse professional opportunities
- general: Access to valuable certifications in latest technologies such as Generative AI
Tags & Categories
Answer 10 quick questions to check your fit for GCP Data Engineer @ Capgemini.
10 Questions
~2 Minutes
Instant Score
Related Books and Jobs