Senior Data Engineer

What you'll do...

Position: Senior Data Engineer

Job Location: 1375 Crossman Avenue, Sunnyvale, CA 94089

Duties: Data Strategy: Understand, articulate, and apply principles of the defined strategy to routine business problems that involve a single function. Data Source Identification: Support the understanding of the priority order of requirements and service level agreements. Helps identify the most suitable source for data that is fit for purpose. Performs initial data quality checks on extracted data. Data Transformation and Integration: Extract data from identified databases. Creates data pipelines and transform data to a structure that is relevant to the problem by selecting appropriate techniques. Develops knowledge of current data science and analytics trends. Tech. Problem Formulation: Translate/ co-own business problems within one's discipline to data related or mathematical solutions. Identifies appropriate methods/tools to be leveraged to provide a solution for the problem. Shares use cases and gives examples to demonstrate how the method would solve the business problem. Understanding Business Context: Provide recommendations to business stakeholders to solve complex business issues. Develops business cases s for projects with a projected return on investment or cost savings. Translates business requirements into projects, activities, and tasks and aligns to overall business strategy and develops domain specific artifact. Serves as an interpreter and conduit to connect business needs with tangible solutions and results. Identify and recommend relevant business insights pertaining to their area of work. Data Modeling: Analyze complex data elements, systems, data flows, dependencies, and relationships to contribute to conceptual, physical, and logical data models. Develops the Logical Data Model and Physical Data Models including data warehouse and data mart designs. Defines relational tables, primary and foreign keys, and stored procedures to create a data model structure. Evaluates existing data models and physical databases for variances and discrepancies. Develops efficient data flows. Analyzes data-related system integration challenges and proposes appropriate solutions. Creates training documentation and trains end-users on data modeling. Oversees the tasks of less experienced programmers and stipulates system troubleshooting supports. Code Development and Testing: Write code to develop the required solution and application features by determining the appropriate programming language and leveraging business, technical, and data requirements. Creates test cases to review and validate the proposed solution design. Creates proofs of concept. Tests the code using the appropriate testing approach. Deploys software to production servers. Contributes code documentation, maintains playbooks, and provides timely progress updates. Data Governance: Establish, modify, and document data governance projects and recommendations. Implements data governance practices in partnership with business stakeholders and peers. Interprets company and regulatory policies on data. Educates others on data governance processes, practices, policies, and guidelines. Provides recommendations on needed updates or inputs into data governance policies, practices, or guidelines. Demonstrates up-to-date expertise and applies this to the development, execution, and improvement of action plans by providing expert advice and guidance to others in the application of information and best practices; supporting and aligning efforts to meet customer and business needs; and building commitment for perspectives and rationales.

Minimum education and experience required: Bachelor’s degree or the equivalent in Computer Science, Information Technology, Engineering, or a related field plus 3 years of experience in software engineering or related experience; OR Master's degree or the equivalent in Computer Science, Information Technology, Engineering, or a related field plus 1 year experience of in software engineering or related experience.

Skills required: Must have experience with: ETL processes and tools to efficiently extract, transform, and load data into data lakes or data warehouses; Data modeling techniques, creating data pipelines, and designing scalable data architectures; Problem-solving and a