Chubb is looking to ensure the smooth operation of their North America enterprise data warehouse, including incident management, performance optimization, and data quality maintenance.
Requirements
- Strong understanding of ETL development concepts and tools such as ETL development solutions (Informatica/IICS)
- Experience with Data Warehousing and Cloud Technologies like Azure (Synapse, Data bricks, Snowflake)
- Experience with scheduling jobs using Autosys (or comparable distributed scheduler)
- Experience writing Unix/Linux or Windows Scripts in tools such as PERL, Shell script, Python, etc.
- Experience creating complex technical specifications from business requirements/specifications
- Strong understanding of data warehouse technologies, ETL processes, and database management systems
Responsibilities
- Lead the process of identifying, prioritizing, and resolving production issues
- Investigate and identify the root causes of incidents to prevent recurrence
- Implement performance tuning techniques to optimize query execution times, ETL processes, and overall system performance
- Implement and maintain data validation processes to ensure the accuracy and integrity of data in the data warehouse
- Address data quality issues, including data cleansing and transformation, to ensure data accuracy and consistency
- Participate in the planning and execution of data warehouse releases
- Test new releases and changes to the data warehouse environment to ensure stability and functionality
Other
- Lead and mentor team members, providing guidance and support as needed
- Build and maintain strong relationships with business users, IT teams, and other stakeholders
- Maintain comprehensive documentation of the data warehouse architecture, processes, and procedures
- Bachelor’s degree required in Computer Science, Computer Information Systems, Information Systems, Information Technology or Computer Engineering or equivalent work experience
- Excellent communication and interpersonal skills
- Experience leading a team and providing technical guidance to junior data engineers
