Data Science Engineer
Capgemini
Data Science Engineer
Job Description
Data Science Engineer
📋 Job Overview
The Data Science Engineer role at Capgemini involves designing and maintaining data pipelines, ensuring data quality, and building and deploying machine learning models into production. The position requires collaboration with data scientists and engineers to deliver end-to-end solutions while researching new technologies for data processing. This role offers opportunities to work on cutting-edge projects in a supportive, inclusive environment.
📍 Location: Bangalore
💼 Experience Level: Experienced Professionals
🏢 Business Unit: Other Delivery units
🎯 Key Responsibilities
- Design and maintain data pipelines for ingestion, transformation, and storage
- Ensure data quality, integrity, and security across systems
- Build and deploy machine learning models and integrate them into production environments
- Optimize model performance and monitor reliability
- Work with structured and unstructured data for analytics and modelling
- Collaborate with data scientists, analysts, and software engineers to deliver end-to-end solutions
- Research and implement new technologies for data processing and automation
✅ Required Qualifications
- 3–5 years of experience in data engineering or data science roles
- Strong programming skills in Python, SQL
- Hands-on experience with cloud platforms (AWS, GCP, Azure)
- Experience with data engineering tools (e.g., Spark, Airflow, Kafka, Snowflake, Databricks)
- Solid understanding of machine learning algorithms and MLOps best practices
- Strong analytical and problem-solving skills
⭐ Preferred Qualifications
- Familiarity with Java/Scala
- Experience with containerization and orchestration (Docker, Kubernetes)
🛠️ Required Skills
- Python
- SQL
- Java/Scala
- AWS
- GCP
- Azure
- Spark
- Airflow
- Kafka
- Snowflake
- Databricks
- Machine learning algorithms
- MLOps best practices
- Docker
- Kubernetes
- Analytical skills
- Problem-solving skills
🎁 Benefits & Perks
- Inclusive and supportive work environment where people of all backgrounds feel encouraged and have a sense of belonging
- Valued for who you are and can bring your original self to work
- Weekly musical performances by in-house band - The Rubber Band every Monday
- Participation in internal sports events, yoga challenges, or marathons
- Work on cutting-edge projects in tech and engineering with industry leaders
- Create solutions to overcome societal and environmental challenges
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
- Pythonintermediate
- SQLintermediate
- Java/Scalaintermediate
- AWSintermediate
- GCPintermediate
- Azureintermediate
- Sparkintermediate
- Airflowintermediate
- Kafkaintermediate
- Snowflakeintermediate
- Databricksintermediate
- Machine learning algorithmsintermediate
- MLOps best practicesintermediate
- Dockerintermediate
- Kubernetesintermediate
- Analytical skillsintermediate
- Problem-solving skillsintermediate
Required Qualifications
- 3–5 years of experience in data engineering or data science roles (experience)
- Strong programming skills in Python, SQL (experience)
- Hands-on experience with cloud platforms (AWS, GCP, Azure) (experience)
- Experience with data engineering tools (e.g., Spark, Airflow, Kafka, Snowflake, Databricks) (experience)
- Solid understanding of machine learning algorithms and MLOps best practices (experience)
- Strong analytical and problem-solving skills (experience)
Preferred Qualifications
- Familiarity with Java/Scala (experience)
- Experience with containerization and orchestration (Docker, Kubernetes) (experience)
Responsibilities
- Design and maintain data pipelines for ingestion, transformation, and storage
- Ensure data quality, integrity, and security across systems
- Build and deploy machine learning models and integrate them into production environments
- Optimize model performance and monitor reliability
- Work with structured and unstructured data for analytics and modelling
- Collaborate with data scientists, analysts, and software engineers to deliver end-to-end solutions
- Research and implement new technologies for data processing and automation
Benefits
- general: Inclusive and supportive work environment where people of all backgrounds feel encouraged and have a sense of belonging
- general: Valued for who you are and can bring your original self to work
- general: Weekly musical performances by in-house band - The Rubber Band every Monday
- general: Participation in internal sports events, yoga challenges, or marathons
- general: Work on cutting-edge projects in tech and engineering with industry leaders
- general: Create solutions to overcome societal and environmental challenges
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Answer 10 quick questions to check your fit for Data Science Engineer @ Capgemini.
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Data Science Engineer
Capgemini
Data Science Engineer
Job Description
Data Science Engineer
📋 Job Overview
The Data Science Engineer role at Capgemini involves designing and maintaining data pipelines, ensuring data quality, and building and deploying machine learning models into production. The position requires collaboration with data scientists and engineers to deliver end-to-end solutions while researching new technologies for data processing. This role offers opportunities to work on cutting-edge projects in a supportive, inclusive environment.
📍 Location: Bangalore
💼 Experience Level: Experienced Professionals
🏢 Business Unit: Other Delivery units
🎯 Key Responsibilities
- Design and maintain data pipelines for ingestion, transformation, and storage
- Ensure data quality, integrity, and security across systems
- Build and deploy machine learning models and integrate them into production environments
- Optimize model performance and monitor reliability
- Work with structured and unstructured data for analytics and modelling
- Collaborate with data scientists, analysts, and software engineers to deliver end-to-end solutions
- Research and implement new technologies for data processing and automation
✅ Required Qualifications
- 3–5 years of experience in data engineering or data science roles
- Strong programming skills in Python, SQL
- Hands-on experience with cloud platforms (AWS, GCP, Azure)
- Experience with data engineering tools (e.g., Spark, Airflow, Kafka, Snowflake, Databricks)
- Solid understanding of machine learning algorithms and MLOps best practices
- Strong analytical and problem-solving skills
⭐ Preferred Qualifications
- Familiarity with Java/Scala
- Experience with containerization and orchestration (Docker, Kubernetes)
🛠️ Required Skills
- Python
- SQL
- Java/Scala
- AWS
- GCP
- Azure
- Spark
- Airflow
- Kafka
- Snowflake
- Databricks
- Machine learning algorithms
- MLOps best practices
- Docker
- Kubernetes
- Analytical skills
- Problem-solving skills
🎁 Benefits & Perks
- Inclusive and supportive work environment where people of all backgrounds feel encouraged and have a sense of belonging
- Valued for who you are and can bring your original self to work
- Weekly musical performances by in-house band - The Rubber Band every Monday
- Participation in internal sports events, yoga challenges, or marathons
- Work on cutting-edge projects in tech and engineering with industry leaders
- Create solutions to overcome societal and environmental challenges
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
- Pythonintermediate
- SQLintermediate
- Java/Scalaintermediate
- AWSintermediate
- GCPintermediate
- Azureintermediate
- Sparkintermediate
- Airflowintermediate
- Kafkaintermediate
- Snowflakeintermediate
- Databricksintermediate
- Machine learning algorithmsintermediate
- MLOps best practicesintermediate
- Dockerintermediate
- Kubernetesintermediate
- Analytical skillsintermediate
- Problem-solving skillsintermediate
Required Qualifications
- 3–5 years of experience in data engineering or data science roles (experience)
- Strong programming skills in Python, SQL (experience)
- Hands-on experience with cloud platforms (AWS, GCP, Azure) (experience)
- Experience with data engineering tools (e.g., Spark, Airflow, Kafka, Snowflake, Databricks) (experience)
- Solid understanding of machine learning algorithms and MLOps best practices (experience)
- Strong analytical and problem-solving skills (experience)
Preferred Qualifications
- Familiarity with Java/Scala (experience)
- Experience with containerization and orchestration (Docker, Kubernetes) (experience)
Responsibilities
- Design and maintain data pipelines for ingestion, transformation, and storage
- Ensure data quality, integrity, and security across systems
- Build and deploy machine learning models and integrate them into production environments
- Optimize model performance and monitor reliability
- Work with structured and unstructured data for analytics and modelling
- Collaborate with data scientists, analysts, and software engineers to deliver end-to-end solutions
- Research and implement new technologies for data processing and automation
Benefits
- general: Inclusive and supportive work environment where people of all backgrounds feel encouraged and have a sense of belonging
- general: Valued for who you are and can bring your original self to work
- general: Weekly musical performances by in-house band - The Rubber Band every Monday
- general: Participation in internal sports events, yoga challenges, or marathons
- general: Work on cutting-edge projects in tech and engineering with industry leaders
- general: Create solutions to overcome societal and environmental challenges
Tags & Categories
Answer 10 quick questions to check your fit for Data Science Engineer @ Capgemini.
10 Questions
~2 Minutes
Instant Score
Related Books and Jobs