Equity, 401k matching, consistently voted best places to work!This Jobot Job is hosted by: Amber HeigerickAre you a fit? Easy Apply now by clicking the "Apply Now" button and sending us your resume.Salary: $145,000 - $185,000 per yearA bit about us:We are a fast growing B2B e-commerce platform company with a vibrant culture that focuses on having fun while learning to be the best we can be. If you are looking for opportunities to grow and expand, this is it!Why join us?This is an opportunity to join a rapidly growing international company! We believe that everyone deserves to thrive at the company they are part of! There are no big egos here. We are collaboraters and team players. Do you want to have an impact on business decisions? Are you tried of coming to work and feeling like your ideas are not heard or valued? We want solutioned-oriented problem solvers, critical thinkers, that are passionate about what they do. Competitive Base + EquityGrowth opportunities quickly into management (if you want)Cultrure focused company from the top downJob DetailsAs a Data Warehouse Engineer you will;
You should have experience with the following:
- Design, develop, consolidate, and optimize available data warehouse infrastructure.
- Collaborate with business and technology stakeholders to ensure data warehouse architecture development and utilization.
- Perform the design and extension of data marts, meta data, and data models.
- Ensure all data warehouse architecture codes are maintained in a version control system
Interested in hearing more? Easy Apply now by clicking the "Apply Now" button.
- Performing data warehouse architecture development and management across one or more data warehouse solutions including BigQuery, Synapse, Teradata, Vertica, or Snowflake
- Developing schemas, testing for quality assurance, administering RDBMS, and monitoring of one or more relational databases including Postgres, MySQL, Oracle, or SQL Server
- Business Intelligence Platforms including PowerBI, Tableau, SportFire, QlikView, MicroStrategy, Information Builders, Looker, or Domo
- Amazon AWS, Google Cloud, or Microsoft Azure cloud platforms
- Dimensional modeling techniques and their applications
- SAS and R code used in data processing and modeling tasks
- Hadoop, Impala, Pig, Hive, YARN, and other big data technolog