Job
Description
JOB SUMMARY DESCRIPTION / PRIMARY PURPOSE OF JOB The Data Warehouse Developer participates in the design, development, documentation, and maintenance of data movement, transformation, integration, and analytics solutions. This role works across various platforms and tools in both cloud and on-prem environments. This position will provide 24x7 support for Starkey global facilities as well as HQ. JOB RESPONSIBILITIES/RESULTS Analyze customer requirements and translate them into technical requirements. Code, test, debug, document and implement ETL solutions. Manage delivery to both the functional and non-functional requirements, including performance, scalability, availability, reliability and security. Design and develop solutions that transform and integrate struc tured and semi-structured data across various platforms, including cloud (SaaS/PaaS/IaaS) and on-premises sources and targets. Participate in all Agile ceremonies including the daily SCRUM. Collaborate with infrastructure team, DBAs, and other software developers to assist in resolving problems with software products or company software systems. Work with other technical engineers across IT to develop ETL solutions, and follow corporate standards for databases, data engineering, and analytics. Provide accurate estimates as well as clearly communicating the status of tasks and identification of risks. Complete all phases of SDLC including analysis, design, development, testing and support utilizing Scrum/Agile methodologies. Demonstration of self-driven, highly motivated, and excellent communication skills. Other duties/responsibilities as assigned. JOB REQUIREMENTS Minimum Education, Certification and Experience Requirements Education - 4 year degree or equivalent experience Experience - 4+ years in software development and/or data engineering roles, preferably 3+ years focused on data engineering. Knowledge / Technical Requirements Expertise in data transformations across disparate platforms Expertise in data manipulation with both structured and semi-structured data Expertise in designing and populating data stores for various purposes, including analytics. Expertise in both traditional and newer data architectures (e.g., data lake) Hands-on knowledge of cloud-native data tooling, ideally in Azure, GCP is a bonus. Hands-on knowledge of traditional ETL tooling, such as from Microsoft - SSIS, SSRS, SSAS, and PowerBI Knowledge of Azure Data Factory is a plus. Competencies, Skills & Abilities Ability to create clear presentations and documentation. Self-motivating Build Partnerships with Customers Demonstrate Credibility
