Asks for

The ad says“A Data Engineer on the BW SOON Data Team analyzes data from multiple source systems and designs/models data marts based on business requirements. Strong data analytics and technical skills are a must, along with the ability to create data models, STTMs, and other technical documentation. The Engineer should have strong communication skills and the ability to understand design requirements and existing business processes to lead in the design, development, and implementation of data products — in partnership with business partners and data scientists. In addition, the Engineer should have the following knowledge: 1) Design, develop, monitor, and support ETL/ELT pipelines processing large volumes of enterprise data, with advanced experience using Oracle Data Integrator (ODI). 2) Design and develop enterprise data warehouse and data mart solutions, including data models, STTMs, technical design documents, and data lineage documentation. 3) Analyze and profile data from multiple source systems, including DB2, Oracle, and distributed data platforms. 4) Advanced expertise in SQL and Oracle PL/SQL development, including complex query writing, performance tuning, and optimization. 5) Strong data modeling experience, including dimensional modeling using Kimball methodologies, Third Normal Form (TNF), Data Vault concepts, and Medallion Architecture. 6) Investigate and resolve production issues, data quality concerns, performance bottlenecks, and SLA risks, experience with incident management, root cause analysis, and production support. 7) Collaborate with business partners to translate requirements into scalable data solutions; lead technical discussions and provide guidance on data architecture, modeling, and integration strategies. 8) Experience implementing data quality controls, reconciliation processes, metadata management, and governance standards, along with a strong understanding of data security, access controls, PII protection, and compliance. 9) Support cloud modernization, data migration, and platform transformation initiatives; hands-on experience with multiple cloud platforms (AWS, Azure) preferred. 10) Excellent communication, documentation, stakeholder management, and cross-team collaboration skills. 11) Intermediate - Python development skills for data integration, automation, and analytics. 12) Intermediate - Snowflake, DBT, and related orchestration/version-control tools (e.g., Fivetran, Airflow, GitHub) is a plus.”
The ad says“A Data Engineer on the BW SOON Data Team analyzes data from multiple source systems and designs/models data marts based on business requirements. Strong data analytics and technical skills are a must, along with the ability to create data models, STTMs, and other technical documentation. The Engineer should have strong communication skills and the ability to understand design requirements and existing business processes to lead in the design, development, and implementation of data products — in partnership with business partners and data scientists. In addition, the Engineer should have the following knowledge: 1) Design, develop, monitor, and support ETL/ELT pipelines processing large volumes of enterprise data, with advanced experience using Oracle Data Integrator (ODI). 2) Design and develop enterprise data warehouse and data mart solutions, including data models, STTMs, technical design documents, and data lineage documentation. 3) Analyze and profile data from multiple source systems, including DB2, Oracle, and distributed data platforms. 4) Advanced expertise in SQL and Oracle PL/SQL development, including complex query writing, performance tuning, and optimization. 5) Strong data modeling experience, including dimensional modeling using Kimball methodologies, Third Normal Form (TNF), Data Vault concepts, and Medallion Architecture. 6) Investigate and resolve production issues, data quality concerns, performance bottlenecks, and SLA risks, experience with incident management, root cause analysis, and production support. 7) Collaborate with business partners to translate requirements into scalable data solutions; lead technical discussions and provide guidance on data architecture, modeling, and integration strategies. 8) Experience implementing data quality controls, reconciliation processes, metadata management, and governance standards, along with a strong understanding of data security, access controls, PII protection, and compliance. 9) Support cloud modernization, data migration, and platform transformation initiatives; hands-on experience with multiple cloud platforms (AWS, Azure) preferred. 10) Excellent communication, documentation, stakeholder management, and cross-team collaboration skills. 11) Intermediate - Python development skills for data integration, automation, and analytics. 12) Intermediate - Snowflake, DBT, and related orchestration/version-control tools (e.g., Fivetran, Airflow, GitHub) is a plus.”
The ad says“Oracle, ODI (Oracle data integration), PL-SQL, GitHub”
The ad says“A Data Engineer on the BW SOON Data Team analyzes data from multiple source systems and designs/models data marts based on business requirements. Strong data analytics and technical skills are a must, along with the ability to create data models, STTMs, and other technical documentation. The Engineer should have strong communication skills and the ability to understand design requirements and existing business processes to lead in the design, development, and implementation of data products — in partnership with business partners and data scientists. In addition, the Engineer should have the following knowledge: 1) Design, develop, monitor, and support ETL/ELT pipelines processing large volumes of enterprise data, with advanced experience using Oracle Data Integrator (ODI). 2) Design and develop enterprise data warehouse and data mart solutions, including data models, STTMs, technical design documents, and data lineage documentation. 3) Analyze and profile data from multiple source systems, including DB2, Oracle, and distributed data platforms. 4) Advanced expertise in SQL and Oracle PL/SQL development, including complex query writing, performance tuning, and optimization. 5) Strong data modeling experience, including dimensional modeling using Kimball methodologies, Third Normal Form (TNF), Data Vault concepts, and Medallion Architecture. 6) Investigate and resolve production issues, data quality concerns, performance bottlenecks, and SLA risks, experience with incident management, root cause analysis, and production support. 7) Collaborate with business partners to translate requirements into scalable data solutions; lead technical discussions and provide guidance on data architecture, modeling, and integration strategies. 8) Experience implementing data quality controls, reconciliation processes, metadata management, and governance standards, along with a strong understanding of data security, access controls, PII protection, and compliance. 9) Support cloud modernization, data migration, and platform transformation initiatives; hands-on experience with multiple cloud platforms (AWS, Azure) preferred. 10) Excellent communication, documentation, stakeholder management, and cross-team collaboration skills. 11) Intermediate - Python development skills for data integration, automation, and analytics. 12) Intermediate - Snowflake, DBT, and related orchestration/version-control tools (e.g., Fivetran, Airflow, GitHub) is a plus.”
The ad says“A Data Engineer on the BW SOON Data Team analyzes data from multiple source systems and designs/models data marts based on business requirements. Strong data analytics and technical skills are a must, along with the ability to create data models, STTMs, and other technical documentation. The Engineer should have strong communication skills and the ability to understand design requirements and existing business processes to lead in the design, development, and implementation of data products — in partnership with business partners and data scientists. In addition, the Engineer should have the following knowledge: 1) Design, develop, monitor, and support ETL/ELT pipelines processing large volumes of enterprise data, with advanced experience using Oracle Data Integrator (ODI). 2) Design and develop enterprise data warehouse and data mart solutions, including data models, STTMs, technical design documents, and data lineage documentation. 3) Analyze and profile data from multiple source systems, including DB2, Oracle, and distributed data platforms. 4) Advanced expertise in SQL and Oracle PL/SQL development, including complex query writing, performance tuning, and optimization. 5) Strong data modeling experience, including dimensional modeling using Kimball methodologies, Third Normal Form (TNF), Data Vault concepts, and Medallion Architecture. 6) Investigate and resolve production issues, data quality concerns, performance bottlenecks, and SLA risks, experience with incident management, root cause analysis, and production support. 7) Collaborate with business partners to translate requirements into scalable data solutions; lead technical discussions and provide guidance on data architecture, modeling, and integration strategies. 8) Experience implementing data quality controls, reconciliation processes, metadata management, and governance standards, along with a strong understanding of data security, access controls, PII protection, and compliance. 9) Support cloud modernization, data migration, and platform transformation initiatives; hands-on experience with multiple cloud platforms (AWS, Azure) preferred. 10) Excellent communication, documentation, stakeholder management, and cross-team collaboration skills. 11) Intermediate - Python development skills for data integration, automation, and analytics. 12) Intermediate - Snowflake, DBT, and related orchestration/version-control tools (e.g., Fivetran, Airflow, GitHub) is a plus.”
The ad says“Oracle, ODI (Oracle data integration), PL-SQL, GitHub”
The ad says“Oracle, ODI (Oracle data integration), PL-SQL, GitHub”
The ad says“A Data Engineer on the BW SOON Data Team analyzes data from multiple source systems and designs/models data marts based on business requirements. Strong data analytics and technical skills are a must, along with the ability to create data models, STTMs, and other technical documentation. The Engineer should have strong communication skills and the ability to understand design requirements and existing business processes to lead in the design, development, and implementation of data products — in partnership with business partners and data scientists. In addition, the Engineer should have the following knowledge: 1) Design, develop, monitor, and support ETL/ELT pipelines processing large volumes of enterprise data, with advanced experience using Oracle Data Integrator (ODI). 2) Design and develop enterprise data warehouse and data mart solutions, including data models, STTMs, technical design documents, and data lineage documentation. 3) Analyze and profile data from multiple source systems, including DB2, Oracle, and distributed data platforms. 4) Advanced expertise in SQL and Oracle PL/SQL development, including complex query writing, performance tuning, and optimization. 5) Strong data modeling experience, including dimensional modeling using Kimball methodologies, Third Normal Form (TNF), Data Vault concepts, and Medallion Architecture. 6) Investigate and resolve production issues, data quality concerns, performance bottlenecks, and SLA risks, experience with incident management, root cause analysis, and production support. 7) Collaborate with business partners to translate requirements into scalable data solutions; lead technical discussions and provide guidance on data architecture, modeling, and integration strategies. 8) Experience implementing data quality controls, reconciliation processes, metadata management, and governance standards, along with a strong understanding of data security, access controls, PII protection, and compliance. 9) Support cloud modernization, data migration, and platform transformation initiatives; hands-on experience with multiple cloud platforms (AWS, Azure) preferred. 10) Excellent communication, documentation, stakeholder management, and cross-team collaboration skills. 11) Intermediate - Python development skills for data integration, automation, and analytics. 12) Intermediate - Snowflake, DBT, and related orchestration/version-control tools (e.g., Fivetran, Airflow, GitHub) is a plus.”
The ad says“A Data Engineer on the BW SOON Data Team analyzes data from multiple source systems and designs/models data marts based on business requirements. Strong data analytics and technical skills are a must, along with the ability to create data models, STTMs, and other technical documentation. The Engineer should have strong communication skills and the ability to understand design requirements and existing business processes to lead in the design, development, and implementation of data products — in partnership with business partners and data scientists. In addition, the Engineer should have the following knowledge: 1) Design, develop, monitor, and support ETL/ELT pipelines processing large volumes of enterprise data, with advanced experience using Oracle Data Integrator (ODI). 2) Design and develop enterprise data warehouse and data mart solutions, including data models, STTMs, technical design documents, and data lineage documentation. 3) Analyze and profile data from multiple source systems, including DB2, Oracle, and distributed data platforms. 4) Advanced expertise in SQL and Oracle PL/SQL development, including complex query writing, performance tuning, and optimization. 5) Strong data modeling experience, including dimensional modeling using Kimball methodologies, Third Normal Form (TNF), Data Vault concepts, and Medallion Architecture. 6) Investigate and resolve production issues, data quality concerns, performance bottlenecks, and SLA risks, experience with incident management, root cause analysis, and production support. 7) Collaborate with business partners to translate requirements into scalable data solutions; lead technical discussions and provide guidance on data architecture, modeling, and integration strategies. 8) Experience implementing data quality controls, reconciliation processes, metadata management, and governance standards, along with a strong understanding of data security, access controls, PII protection, and compliance. 9) Support cloud modernization, data migration, and platform transformation initiatives; hands-on experience with multiple cloud platforms (AWS, Azure) preferred. 10) Excellent communication, documentation, stakeholder management, and cross-team collaboration skills. 11) Intermediate - Python development skills for data integration, automation, and analytics. 12) Intermediate - Snowflake, DBT, and related orchestration/version-control tools (e.g., Fivetran, Airflow, GitHub) is a plus.”
The ad says“Oracle, ODI (Oracle data integration), PL-SQL, GitHub”
The ad says“Exp in Production Support”
The ad says“A Data Engineer on the BW SOON Data Team analyzes data from multiple source systems and designs/models data marts based on business requirements. Strong data analytics and technical skills are a must, along with the ability to create data models, STTMs, and other technical documentation. The Engineer should have strong communication skills and the ability to understand design requirements and existing business processes to lead in the design, development, and implementation of data products — in partnership with business partners and data scientists. In addition, the Engineer should have the following knowledge: 1) Design, develop, monitor, and support ETL/ELT pipelines processing large volumes of enterprise data, with advanced experience using Oracle Data Integrator (ODI). 2) Design and develop enterprise data warehouse and data mart solutions, including data models, STTMs, technical design documents, and data lineage documentation. 3) Analyze and profile data from multiple source systems, including DB2, Oracle, and distributed data platforms. 4) Advanced expertise in SQL and Oracle PL/SQL development, including complex query writing, performance tuning, and optimization. 5) Strong data modeling experience, including dimensional modeling using Kimball methodologies, Third Normal Form (TNF), Data Vault concepts, and Medallion Architecture. 6) Investigate and resolve production issues, data quality concerns, performance bottlenecks, and SLA risks, experience with incident management, root cause analysis, and production support. 7) Collaborate with business partners to translate requirements into scalable data solutions; lead technical discussions and provide guidance on data architecture, modeling, and integration strategies. 8) Experience implementing data quality controls, reconciliation processes, metadata management, and governance standards, along with a strong understanding of data security, access controls, PII protection, and compliance. 9) Support cloud modernization, data migration, and platform transformation initiatives; hands-on experience with multiple cloud platforms (AWS, Azure) preferred. 10) Excellent communication, documentation, stakeholder management, and cross-team collaboration skills. 11) Intermediate - Python development skills for data integration, automation, and analytics. 12) Intermediate - Snowflake, DBT, and related orchestration/version-control tools (e.g., Fivetran, Airflow, GitHub) is a plus.”
The ad says“A Data Engineer on the BW SOON Data Team analyzes data from multiple source systems and designs/models data marts based on business requirements. Strong data analytics and technical skills are a must, along with the ability to create data models, STTMs, and other technical documentation. The Engineer should have strong communication skills and the ability to understand design requirements and existing business processes to lead in the design, development, and implementation of data products — in partnership with business partners and data scientists. In addition, the Engineer should have the following knowledge: 1) Design, develop, monitor, and support ETL/ELT pipelines processing large volumes of enterprise data, with advanced experience using Oracle Data Integrator (ODI). 2) Design and develop enterprise data warehouse and data mart solutions, including data models, STTMs, technical design documents, and data lineage documentation. 3) Analyze and profile data from multiple source systems, including DB2, Oracle, and distributed data platforms. 4) Advanced expertise in SQL and Oracle PL/SQL development, including complex query writing, performance tuning, and optimization. 5) Strong data modeling experience, including dimensional modeling using Kimball methodologies, Third Normal Form (TNF), Data Vault concepts, and Medallion Architecture. 6) Investigate and resolve production issues, data quality concerns, performance bottlenecks, and SLA risks, experience with incident management, root cause analysis, and production support. 7) Collaborate with business partners to translate requirements into scalable data solutions; lead technical discussions and provide guidance on data architecture, modeling, and integration strategies. 8) Experience implementing data quality controls, reconciliation processes, metadata management, and governance standards, along with a strong understanding of data security, access controls, PII protection, and compliance. 9) Support cloud modernization, data migration, and platform transformation initiatives; hands-on experience with multiple cloud platforms (AWS, Azure) preferred. 10) Excellent communication, documentation, stakeholder management, and cross-team collaboration skills. 11) Intermediate - Python development skills for data integration, automation, and analytics. 12) Intermediate - Snowflake, DBT, and related orchestration/version-control tools (e.g., Fivetran, Airflow, GitHub) is a plus.”
The ad says“A Data Engineer on the BW SOON Data Team analyzes data from multiple source systems and designs/models data marts based on business requirements. Strong data analytics and technical skills are a must, along with the ability to create data models, STTMs, and other technical documentation. The Engineer should have strong communication skills and the ability to understand design requirements and existing business processes to lead in the design, development, and implementation of data products — in partnership with business partners and data scientists. In addition, the Engineer should have the following knowledge: 1) Design, develop, monitor, and support ETL/ELT pipelines processing large volumes of enterprise data, with advanced experience using Oracle Data Integrator (ODI). 2) Design and develop enterprise data warehouse and data mart solutions, including data models, STTMs, technical design documents, and data lineage documentation. 3) Analyze and profile data from multiple source systems, including DB2, Oracle, and distributed data platforms. 4) Advanced expertise in SQL and Oracle PL/SQL development, including complex query writing, performance tuning, and optimization. 5) Strong data modeling experience, including dimensional modeling using Kimball methodologies, Third Normal Form (TNF), Data Vault concepts, and Medallion Architecture. 6) Investigate and resolve production issues, data quality concerns, performance bottlenecks, and SLA risks, experience with incident management, root cause analysis, and production support. 7) Collaborate with business partners to translate requirements into scalable data solutions; lead technical discussions and provide guidance on data architecture, modeling, and integration strategies. 8) Experience implementing data quality controls, reconciliation processes, metadata management, and governance standards, along with a strong understanding of data security, access controls, PII protection, and compliance. 9) Support cloud modernization, data migration, and platform transformation initiatives; hands-on experience with multiple cloud platforms (AWS, Azure) preferred. 10) Excellent communication, documentation, stakeholder management, and cross-team collaboration skills. 11) Intermediate - Python development skills for data integration, automation, and analytics. 12) Intermediate - Snowflake, DBT, and related orchestration/version-control tools (e.g., Fivetran, Airflow, GitHub) is a plus.”

A Data Engineer on the BW SOON Data Team analyzes data from multiple source systems and designs/models data marts based on business requirements. Strong data analytics and technical skills are a must, along with the ability to create data models, STTMs, and other technical documentation. The Engineer should have strong communication skills and the ability to understand design requirements and existing business processes to lead in the design, development, and implementation of data products — in partnership with business partners and data scientists. In addition, the Engineer should have the following knowledge: 1) Design, develop, monitor, and support ETL/ELT pipelines processing large volumes of enterprise data, with advanced experience using Oracle Data Integrator (ODI). 2) Design and develop enterprise data warehouse and data mart solutions, including data models, STTMs, technical design documents, and data lineage documentation. 3) Analyze and profile data from multiple source systems, including DB2, Oracle, and distributed data platforms. 4) Advanced expertise in SQL and Oracle PL/SQL development, including complex query writing, performance tuning, and optimization. 5) Strong data modeling experience, including dimensional modeling using Kimball methodologies, Third Normal Form (TNF), Data Vault concepts, and Medallion Architecture. 6) Investigate and resolve production issues, data quality concerns, performance bottlenecks, and SLA risks, experience with incident management, root cause analysis, and production support. 7) Collaborate with business partners to translate requirements into scalable data solutions; lead technical discussions and provide guidance on data architecture, modeling, and integration strategies. 8) Experience implementing data quality controls, reconciliation processes, metadata management, and governance standards, along with a strong understanding of data security, access controls, PII protection, and compliance. 9) Support cloud modernization, data migration, and platform transformation initiatives; hands-on experience with multiple cloud platforms (AWS, Azure) preferred. 10) Excellent communication, documentation, stakeholder management, and cross-team collaboration skills. 11) Intermediate - Python development skills for data integration, automation, and analytics. 12) Intermediate - Snowflake, DBT, and related orchestration/version-control tools (e.g., Fivetran, Airflow, GitHub) is a plus.

Requirements

Oracle, ODI (Oracle data integration), PL-SQL, GitHub
Exp in Production Support

Benefits

Competitive compensation and benefits package:

Competitive salary and performance-based bonuses
Comprehensive benefits package
Career development and training opportunities
Flexible work arrangements (remote and/or office-based)
Dynamic and inclusive work culture within a globally renowned group
Private Health Insurance
Pension Plan
Paid Time Off
Training & Development

Note: Benefits differ based on employee level.

About Capgemini

Capgemini is a global leader in partnering with companies to transform and manage their business by harnessing the power of technology. The Group is guided everyday by its purpose of unleashing human energy through technology for an inclusive and sustainable future. It is a responsible and diverse organization of over 340,000 team members in more than 50 countries. With its strong 55-year heritage and deep industry expertise, Capgemini is trusted by its clients to address the entire breadth of their business needs, from strategy and design to operations, fueled by the fast evolving and innovative world of cloud, data, AI, connectivity, software, digital engineering and platforms. The Group €22.5 billion in revenues in 2023.

https://www.capgemini.com/us-en/about-us/who-we-are/