Our client is one of the largest retailers in Canada. With a strong team, they focus on not only bringing in the right technical talent, but also the right personalities. The right candidate will be focused on contributing to the environment as part of a team. Our client is growing and looking for a Senior Data integration Analyst to join the team on a permanent basis.
What's in it for you?
Our client is located in Saskatchewan and offers a competitive compensation, relocation package & employee benefits plan as well as an RRSP. At the same time, our client empowers its teams to harness new ideas, and allows staff unleash their imaginations to cr
- Analyze business requirements to design highly efficient, highly scalable ETL processes.
- Work with Business Analysts to identify and understand source systems, target systems, and source-to-target data mapping matrix.
- Develop and implement ETL solutions to meet project requirements.
- Create test plans, test cases, and test scripts; perform unit and integration testing; and support Quality Assurance and User Acceptance Testing.
- Participate in project planning and scheduling by providing status updates, and identifying and resolving project risks and issues.
- Administer and monitor ETL platform and other data integration tools.
- Analyze and recommend ETL design and performance enhancements for operational processes (i.e. large data volume loads and length process, capacity planning, etc.).
- Identify opportunities for data quality improvement for DW/BI related applications.
- Identify the need for appropriate data integration tools (i.e. data quality, job scheduling, and testing for DW/BI development and operations).
- A Bachelor's degree in Computer Science or a related field; an equivalent combination of relevant education and experience may be considered.
- 10-13 years IT experience, including: 5+ years in Informatica; 5+ years in databases such as DB2, Oracle, and SQLServer).
- Experience in data architecture (Data Warehousing; ODS; Data Marts; Staging; MDM; Data Quality Process).
- Experience in different software development methodologies, such as agile, iterative and warerfall methodology.
- Experience in Software Quality Assurance practices.
- Experience in handling complex unstructured data and Mainframe, as well as Informatica certification will be considered an asset