Data Engineer - Data Analytics / BI

REMOTE. Must have 5 years of experience in design, development, and support of terabyte scale data warehouses. Strong SQL programming skills. Strong understanding of relational and dimensional modeling, data mining, and ETL design processes. SUMMARY STATEMENT: The Data Engineer is a key role in technology initiatives to advance health informatics and analytics in the health sciences by improving the usability, performance, and overall architecture of the enterprise data warehouse. This role develops data extraction, transformation, and load processes between source and target data structures, and supports junior developers in the development of the data warehouse, in collaboration with data architecture and other stakeholders. The developer is also an active participant in data modeling and data mapping exercises. The candidate is expected to write efficient and highly performant code that is scalable and possess a thorough knowledge of the internal workings of SQL Server and other database systems. The Data Engineer supports UCLA Health Sciences initiatives that drive clinical, financial, and operational improvement. The incumbent is expected to understand the clinical, financial, and operational issues to be solved and to determine targeted individual and/or linked healthcare data sets (structured and unstructured). TYPE OF SUPERVISION RECEIVED: The Data Engineer receives overall objectives, deliverables, and priorities from the Manager of Data Architecture. The individual is expected to determine the most effective method to accomplish assigned tasks within the allowed timeframes and to work independently with minimal supervision. The individual obtains review and approval of key deliverables from the manager and others as required and is expected to seek guidance on balancing competing priorities or issues. KEY RESPONSIBILITIES: Contribute to ongoing development of technical best practices for data movement, data quality, data cleansing, and other ETL-related activities. Create automated processes to validate and translate data for landing in the enterprise data warehouse. Review requirements and participate in the design of data models. Design and Build Master Data Models for Reference datasets like Providers and Payors. Develop and consume REST APIs to ingest data from third-party sources. Design and develop new data processing systems using various ETL tools and languages like Python/SSIS and open-source technologies. Design and develop data pipelines and processes that effectively populate the enterprise data warehouse and downstream data marts. Participate in meetings with technical peers regarding solution design. Communicate with business analysts, data modelers, and solutions architects regarding specific development activities and ETL. Understand and implement best practices for tuning and optimization. Develop and maintain both source code and related documents. Translate advanced business analytics problems into technical approaches that yield actionable recommendations. Maintain technical proficiency in data warehousing technologies beyond the classic Microsoft Stack such as Big Data and cloud technologies. Work with organizational stakeholders to identify business requirements and expected outcomes. Create clear documentation of workflows, process flows, methodologies used, and complex logic for various levels of technical expertise. Collaborate with other UCLA Health IT teams (OHIA, ISS, and DGIT). SKILLS, KNOWLEDGE AND ABILITIES: Five plus years of strong work experience in the design, development, and support of terabyte scale data warehouses. Strong SQL programming skills, particularly in Microsoft SQL Server and Oracle. Strong understanding of relational and dimensional modeling, data mining, and ETL design processes. Experience in Master Data Management and Data Quality initiatives is highly preferred. Programming expertise in languages like C# or Python. Strong experience in Business Intelligence tools like SSIS, SSRS, and SSAS. Expertise in database architecture, storage, and Query Optimizer. Good architectural understanding of reporting tools like Tableau and PowerBI. Experience working in an agile software development environment is a plus. Work experience with healthcare data is preferred. #J-18808-Ljbffr