Sr. Data Warehouse Engineer
RootMetrics - Bellevue, WA

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We’re seeking a self-motivated Senior Data Warehouse Engineer experienced in end-to-end data warehouse development to extend our capabilities in data platform, ETL tools, and big data capabilities.

Key Responsibilities
  • Design and implement ETL/Business Intelligence solutions for various business stakeholders including Marketing, Operations and Product
  • Coordinate and liaise with business analysts, product and program management functions on data/functional requirements
  • Enhance and support the current warehouse systems and continue to extend the capabilities into the big data domain
  • Develop the data API via stored procedures for business tools to automate and manage all of the facets of business and data analytics operations
  • Work closely with QA engineers to define test cases, test strategy, entry and exit criteria on ETL/data testing
  • Build and define the Warehouse SLA to support Engineering operation efficiencies
  • Perform process, query, database tuning as needed on the current data platform
  • Build and design the coding standards for ETL, data modeling, and stored procedures
Required Skills
  • BS in Computer Science or Engineering or equivalent experience
  • Minimum 5 years computer programming with an emphasis on data warehousing
  • Data modeling skills involving OLAP and OLTP and its complexity interfacing ETL or BI tools
  • Experienced in data modeling for Metadata and Data Warehouse involving slowly changing dimension
  • Experienced in Source-to-Target mapping and data profiling assessment on various data platform
  • Experienced in writing efficient SQL and stored procedures (including analytic functions, CTE) against VLDB
  • Experienced in NoSQL database such as MongoDB
  • Capability to tune and optimize schema design
  • Experience troubleshooting large data warehouses and associated sub-systems
  • Experienced in data recovery strategies and mitigation
  • Development of tools and/or stored procedures that enable and streamline analysts’ access to data
  • Preference to work in a nimble and dynamic environment, with strong emphasis on ownership and responsibility
Skills Appreciated
  • Understanding of statistics and data analytics
  • Proficiency in big data (NoSQL databases, Hadoop, Pub-Sub, et al)
  • Experience programming in the Linux environment (Python preferred)
  • Collaboration methodologies using Git
  • Strong communication and organizational skills