Vacancy expired!
- Any OLAP data modeling experience is valuable.
- Couple of lines in physical data modeling.
- Not an implementation team.
- Designing and producing the data models.
- Don’t do production support and software installs at night.
- SQL- Any analysis SQL skills, Querying databases. Some coding experience. GAP analysis on existing databases. Creating sample data sets for consumer
- Physical Modeling- Diametrical data modeling. Special type of data modeling for analytics and reporting teams. Will need to create new physical data models to support data migration.
- Bachelor’s Degree or equivalent in a technology related field (e.g. Computer Science, Engineering, etc.) with a focus on data analysis, data structures, or data modeling.
- Expert level analysis skills in the form of research, gap analysis, data mining, and data profiling.
- Solid understanding of data lineage. Ability to breakdown and detail the flow of data from origination to consumption.
- Proven track record of solving real world problems using a design-oriented modeling approach in large data warehouses, data marts, and analytics/reporting platforms.
- Understanding of different database platforms (e.g. Oracle, Snowflake, Hadoop, Microsoft SQL Server) usages (OLTP Recordkeeping, ODS, MDM, Warehousing, and Data Lakes).
- Understanding of modeling strategies (dimensional, relational, unstructured).
- Robust SQL experience, used to design new platforms on cloud technologies/architecture including Snowflake, AWS, etc.
- Proficient with ERD/Data Modeling tools (e.g. SAP Power Designer or Erwin).
- Experience carrying out projects in an Agile environment.
- Having outstanding interpersonal skills with experience collaborating and influencing across all levels of the organization including written, verbal, and technology illustrations.
- Perform autonomously on tasks but are willing and able to share knowledge with coworkers and partners.
- Go-getter, self-sufficient, and willing to exhaust all research avenues before seeking help or discontinuing the search for answers.
- Accepts uncertainty and can combine various sources of information including personal data experimentation, research, and dialogues to formulate answers.
- Values pace over perfection and can show incremental progress of analysis and research through tangible artifacts.
- Capable of balancing multiple contending priorities.
- Familiar with the financial industry and/or have a strong desire to learn our brokerage business to enhance the value of our data.
- Experience with cloud native data warehousing and data lake solutions using Snowflake is a plus.
- Experience with Kimball Data Warehouse design techniques.