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Guidewire DH

at Capgemini

Back to all Data Engineering jobs
Capgemini logo
Consultancies

Guidewire DH

at Capgemini

Mid LevelNo visa sponsorshipData Engineering

Posted 5 days ago

No clicks

Compensation
Not specified

Currency: Not specified

City
Not specified
Country
Not specified

Data engineers are responsible for building reliable and scalable data infrastructure that enables organizations to derive meaningful insights and make data-driven decisions. The role focuses on designing, developing, and optimizing data infrastructure and systems to enhance data processes and leverage data effectively to drive business outcomes. This position emphasizes data architecture, governance, and integration across platforms to unlock the value of data assets. It is part of Capgemini's Hyderabad team, collaborating with cross-functional groups to deliver robust data solutions.

Job Description

Data engineers are responsible for building reliable and scalable data infrastructure that enables organizations to derive meaningful insights, make data-driven decisions, and unlock the value of their data assets.

Job Description - Grade Specific

The primary focus is to help organizations design, develop, and optimize their data infrastructure and systems. They help organizations enhance data processes, and leverage data effectively to drive business outcomes.

Skills (competencies)

Industry Standard Data Modeling (FSLDM)
Ab Initio
Industry Standard Data Modeling (IBM FSDM))
Agile (Software Development Framework)
Influencing
Apache Hadoop
Informatica IICS
AWS Airflow
Inmon methodology
AWS Athena
JavaScript
AWS Code Pipeline
Jenkins
AWS EFS
Kimball
AWS EMR
Linux - Redhat
AWS Redshift
Negotiation
AWS S3
Netezza
Azure ADLS Gen2
NewSQL
Azure Data Factory
Oracle Exadata
Azure Data Lake Storage
Performance Tuning
Azure Databricks
Perl
Azure Event Hub
Platform Update Management
Azure Stream Analytics
Project Management
Azure Sunapse
PySpark
Bitbucket
Python
Change Management
R
Client Centricity
RDD Optimization
Collaboration
SantOs
Continuous Integration and Continuous Delivery (CI/CD)
SaS
Data Architecture Patterns
Scala Spark
Data Format Analysis
Shell Script
Data Governance
Snowflake
Data Modeling
SPARK
Data Validation
SPARK Code Optimization
Data Vault Modeling
SQL
Database Schema Design
Stakeholder Management
Decision-Making
Sun Solaris
DevOps
Synapse
Dimensional Modeling
Talend
GCP Big Table
Teradata
GCP BigQuery
Time Management
GCP Cloud Storage
Ubuntu
GCP DataFlow
Vendor Management
GCP DataProc
Git
Google Big Tabel
Google Data Proc
Greenplum
HQL
IBM Data Stage
IBM DB2

Guidewire DH

at Capgemini

Back to all Data Engineering jobs
Capgemini logo
Consultancies

Guidewire DH

at Capgemini

Mid LevelNo visa sponsorshipData Engineering

Posted 5 days ago

No clicks

Compensation
Not specified

Currency: Not specified

City
Not specified
Country
Not specified

Data engineers are responsible for building reliable and scalable data infrastructure that enables organizations to derive meaningful insights and make data-driven decisions. The role focuses on designing, developing, and optimizing data infrastructure and systems to enhance data processes and leverage data effectively to drive business outcomes. This position emphasizes data architecture, governance, and integration across platforms to unlock the value of data assets. It is part of Capgemini's Hyderabad team, collaborating with cross-functional groups to deliver robust data solutions.

Job Description

Data engineers are responsible for building reliable and scalable data infrastructure that enables organizations to derive meaningful insights, make data-driven decisions, and unlock the value of their data assets.

Job Description - Grade Specific

The primary focus is to help organizations design, develop, and optimize their data infrastructure and systems. They help organizations enhance data processes, and leverage data effectively to drive business outcomes.

Skills (competencies)

Industry Standard Data Modeling (FSLDM)
Ab Initio
Industry Standard Data Modeling (IBM FSDM))
Agile (Software Development Framework)
Influencing
Apache Hadoop
Informatica IICS
AWS Airflow
Inmon methodology
AWS Athena
JavaScript
AWS Code Pipeline
Jenkins
AWS EFS
Kimball
AWS EMR
Linux - Redhat
AWS Redshift
Negotiation
AWS S3
Netezza
Azure ADLS Gen2
NewSQL
Azure Data Factory
Oracle Exadata
Azure Data Lake Storage
Performance Tuning
Azure Databricks
Perl
Azure Event Hub
Platform Update Management
Azure Stream Analytics
Project Management
Azure Sunapse
PySpark
Bitbucket
Python
Change Management
R
Client Centricity
RDD Optimization
Collaboration
SantOs
Continuous Integration and Continuous Delivery (CI/CD)
SaS
Data Architecture Patterns
Scala Spark
Data Format Analysis
Shell Script
Data Governance
Snowflake
Data Modeling
SPARK
Data Validation
SPARK Code Optimization
Data Vault Modeling
SQL
Database Schema Design
Stakeholder Management
Decision-Making
Sun Solaris
DevOps
Synapse
Dimensional Modeling
Talend
GCP Big Table
Teradata
GCP BigQuery
Time Management
GCP Cloud Storage
Ubuntu
GCP DataFlow
Vendor Management
GCP DataProc
Git
Google Big Tabel
Google Data Proc
Greenplum
HQL
IBM Data Stage
IBM DB2