Enter a job title or keyword
Siebel Administrator
Job Location:
Monthly Salary:
CAD 1695000000004823 - 1695000000004823
Monthly Salary:
Experience Required:
5years
Experience Required:
Posted:
19 June 2026 (30+ days ago)
Posted:
Application Deadline:
16 September 2026
Application Deadline:
Vacancies:
1 Vacancy
Vacancies:
Job Summary
Role: Siebel Administrator
Location: Toronto ON
Work Model: Hybrid (2 days/week in-office preferred)
Experience Required: 6-8 Years
Required Skills
- Oracle SQL
- Oracle Siebel Functional Customer Order Management
- Unix/Linux Basics and Commands
Top 3 Required Skills
- Oracle SQL & PL/SQL Development Strong expertise in writing optimizing and maintaining stored procedures packages and complex queries.
- Linux System Administration Advanced knowledge of configuration maintenance security networking and troubleshooting (10 years of experience level).
- Siebel Administration & Support Hands-on experience with Siebel CRM environment management configuration and issue resolution.
Top 3 Preferred Skills
- Middleware Technologies (IBM MQ WebSphere IHS) Installation configuration and ongoing maintenance.
- Shell Scripting (Bash/Ksh) Automation of deployments monitoring and system tasks.
- Database & Client Configuration / Integration Skills DB connectivity setup cross-system integration and troubleshooting.
Roles & Responsibilities
- Siebel Administration.
- Installation and maintenance of MQ WebSphere IHS and Siebel in Linux systems.
- Good skills in SQL/PLSQL.
- 10 years of experience in Linux Administration involving configuration maintenance security and networking (equivalent to Windows clustering).
- Skills in shell scripting and DB client configuration.
Required Skills:
60-70
Required Education:
Job Overview:Were seeking an experienced ETL Pipeline Developer proficient in Python to design implement and maintain robust data pipelines. This role is critical for transforming raw data into valuable business insights across our Responsibilities: Architect and build efficient ETL pipelines in Python to process diverse data sources Implement data transformation logic using pandas for complex manipulations and aggregations Document pipeline architecture data flows
