Data Engineer

Job Title- Data Engineer 5 Location- Beaverton, OR, United States, 97005 Reporting Type- Onsite Duration: 9+ Months • W2 candidates only • • No C2C or Third Party vendors • Summary GT Title: Data Engineer Requirements Typically requires a Bachelors Degree and minimum of 10 years directly relevant experience; experience should include comprehensive experience as a business/process leader or industry expert Note: One of the following alternatives may be accepted: - PhD or Law + 8 yrs; Masters + 9 yrs; Associates degree + 11 yrs; High School + 12 yrs. Comments for Suppliers: Must be onsite at Client HQ in Beaverton for Hybrid schedule, 4:1. Data engineers build and maintain systems that collect, manage, and transform data into usable information. They work with large amounts of data from various sources, and ensure that data is accessible and flows smoothly to its destination. Must have 4-6 years of experience with: Databricks AWS Apache Spark Python PySpark Previous Clients experience a plus. Any ETWs let go at the end of 05/31 can be considered since a 90 day break would be fulfilled. Skills Data engineer Responsibilities Establishes database management systems, standards, guidelines and quality assurance for database deliverables, such as conceptual design, logical database, capacity planning, external data interface specification, data loading plan, data maintenance plan and security policy. Documents and communicates database design. Evaluates and installs database management systems. Codes complex programs and derives logical processes on technical platforms. Builds windows, screens and reports. Assists in the design of user interface and business application prototypes. Participates in quality assurance and develops test application code in client server environments. Provides expertise in devising, negotiating and defending the tables and fields provided in the database. Adapts business requirements, developed by modeling/development staff and systems engineers, and develops the data, database specifications, and table and element attributes for an application. At more experienced levels, helps to develop an understanding of client's original data and storage mechanisms. Determines appropriateness of data for storage and optimum storage organization. Determines how tables relate to each other and how fields interact within the tables for a relational model.