Data Engineer III

Les Schwab Tire Centers bring you the best selection, quality, and service every time on tires, brakes, wheels, batteries, shocks, and alignment services. Job Description POSITION SUMMARY: Data Engineers provide data services to stakeholders within portfolios and throughout the enterprise by building and managing data resources to support reporting, business intelligence, analytics, data science projects and operational applications. They engage with data-centric product managers and developers, technology teams, analysts, and business partners to understand capability requirements and define and construct data structures and solutions based on priorities. The Data Engineer III has advanced proficiency in the design, development, and operational tasks required to provide accurate, timely, high quality data critical to feed data products (reports, analyses and data science models) and support downstream applications. The Data Engineer III has deep understanding of available business data resources and how to craft robust, practical data solutions and works with business stakeholders and technical counterparts on best practices for stewardship, building and maintaining data resources. This role is within the Information and Digital Services organization at Les Schwab headquarters in Bend, OR. PRIMARY RESPONSIBILITIES/FUNCTIONS 20% Operational Support Build and deliver ad hoc data sets to support business analysis, data analysis, analytics, proofs-of-concept, and other use cases Create and review complex SQL scripts and queries in support of reporting and analytics applications Evaluate and implement appropriate technologies and methods to automate data preparation and data movement with Les Schwab standard data stores, tools, and platforms Monitor and troubleshoot manual and automated data preparation and data movement processes Solve complex technical problems and mentor/support other technical staff in developing workarounds and resolving operational issues Create, maintain and review operational procedures and related documentation 30% Data Structure and Solution Design Collaborate with business systems analysts, data analysts, business stakeholders, and analytics practitioners to understand data product and downstream system data requirements Collaborate with data stewards and data source managers to understand data definitions and business rules relevant to data structure design Perform detailed design of data structures from inception through production support Create data models for relational and dimensional database schemas for a range of use cases from targeted reporting solutions to support of downstream applications Conduct information modeling, including conceptual models, relational database designs and message models Perform and review designs and solutions for data manipulation, data preparation, and data movement processes for a variety of scenarios from simple file-based export/import to enterprise-grade ETL workflows connecting multiple structured and unstructured endpoints 20% Data Structure and Solution Development Catalog existing data sources and enable access to resident and external data sources Develop programming, modeling and data integration, supporting task automation Create physical database tables, views, and flat files for analytics research projects, reporting, analytics applications, and for publication to downstream subscribers Solve complex technical problems and mentor/support other technical staff in developing data models, data structures and ETL solutions Create and maintain data dictionaries, data model diagrams, data mapping documents, data security and quality requirements and related data platform documentation Work in an agile team environment to deliver timely analytics solutions and insights within a dynamic learning organization 15% Data Platform Quality and Governance Develop a quality assurance framework to ensure the delivery of high quality data and data structure analyses to stakeholders Collaborate with Digital Services colleagues to select and adopt best practices within a culture of data management excellence Implement and continuously improve development best practices, version control and deployment strategies to ensure product quality, agility and recoverability Implement and test data access roles and permissions to ensure "least privileged" access to enterprise data and reduce the enterprise risk of data exposure Proactively identify opportunities to improve data workflows and query performance 10% Stakeholder Relationship and Vendor Management Support Data Stewards to establish and enforce guidelines for data collection, integration and maintenance Provide expert advice to empower Information and Digital Services colleagues to understand and utilize Enterprise Data Platform Services and Data resources Collaborate with Portfolios across the enterprise to ensure that roles for data access follow "least privilege" principles, yet there is high data literacy and awareness of enterprise data available for use Make all stakeholders ethically aware of the unintended consequences of the use of data and identify risks and opportunities to be communicated throughout the enterprise 5% Resource Development: Mentoring and Best Practices Provide mentoring and expert advice for the development of complex and high-performance SQL Promote best practices for building quality into data structure, ETL and data solutions to improve efficiency and lower probabilities of defects within the data platform and downstream Move beyond the scope of individual projects and promote, guard and guide the organization toward common semantics and proper use of metadata Take responsibility for streamlining data pipelines across the enterprise, ensuring they are coordinated, consistent, efficient and production ready Qualifications Educational/Experience Requirements: Bachelor’s degree (BS or BA) in STEM related discipline with major in Computer Science, Information Management, Database Development and Analysis or equivalent disciplines or equivalent experience with appropriate time-in-role 6+ years of experience with data warehouse technical architectures, ETL/ELT, reporting/analytic tools and scripting Experience with AWS services including S3, Data-pipeline and cloud based data warehouses Experience with data visualization tools such as Tableau or Birst is a plus #J-18808-Ljbffr