This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description This role involves working as a Data Engineer at Royal Credit Union, where you will help build the cloud-based Business Intelligence platform, solve complex analytical challenges, and create data systems that empower teams across the organization. - Analyze and transform raw data into useful cloud-based data systems. - Support line of business for all quantitative needs, including leading mid-size initiatives. - Involve increasingly complex levels of data and statistical analysis. - Resolve issues that may require in-depth quantitative analysis with non-routine solutions. Qualifications - Bachelor’s Degree or equivalent experience in software engineering, data engineering, data science, information systems, computer science, mathematics, machine learning, or related field of study. - Three years’ experience in data engineering, data science, or software engineering, including knowledge of extensive data ecosystems. - Must be bondable. Requirements - Advanced data architecture and system design expertise, including experience with multiple file structures (flat files, JSON, XML). - Experience building and maintaining cloud-based data systems and developing scalable data infrastructures, pipelines, and warehouses. - Proficiency in modern programming and analytical tools, including strong skills in SQL, R, and/or Python. - Strong data connectivity and integration capabilities, including working with APIs (REST/SOAP), ODBC/JDBC, and HTTP webhooks. - Effective communication and collaboration abilities, including summarizing technical concepts for non-technical audiences. - Experience working within Agile environments (Azure DevOps) and using version control (Git, Kubernetes). - Exceptional problem-solving and adaptability skills, with the ability to perform root-cause analysis and handle ambiguity. Benefits - Comprehensive medical, dental, and vision insurance plans. - 5% 401k employer match. - Paid family and sick leave. - Vacation and sick time accruals. - Childcare reimbursement. - Tuition and student loan debt assistance. - Pet insurance. - And much more! Work Schedule - This is a full-time, exempt level position. - Hours will generally be Monday through Friday, 8:00am – 5:00pm with occasional evening and weekend hours as needed. - This position is eligible to be fully remote within the United States. Training - New Royal team members must attend Foundation Training at the Corporate Center in Eau Claire, WI during their first week of employment. - Foundation Training covers fundamental information about Royal’s culture and core values. - Out of town learners will be reimbursed costs related to travel and lodging.

• Perform data engineering tasks, including data modeling, data pipeline development, and cube development • Work with relational databases, including schema design, queries, views, store procedures, and performance optimization • Data governance and master data management • Build data pipelines that execute ETL/ELT processes to move and integrate data between data sources • Conduct DevOps activities, including code reviews, testing, alerting, documenting, retrospectives, incident analysis • Work with Azure's core data and analysis services, including Data Factory, Synapse Analytics, Data Explorer, Power BI, etc. • Build data warehouses, including the use of ETL/ELT, SQL, Data Lake, Spark, Azure Synapse, Databricks, tabular cubes.

• Plan and align the project with the Androidization strategy • Gather and validate functional and technical requirements • Design the solution architecture and data model • Automate the integration and processing of operational data • Model and automate refined tables with business rules • Implement monitoring and proactive alerts • Publish and validate the tables in the production environment • Document the full technical and functional architecture of the platform • Conduct training sessions and formalize the technical handover

• Planejar e alinhar o projeto com a estratégia de Androidização • Coletar e validar requisitos funcionais e técnicos • Desenhar a arquitetura da solução e o modelo de dados • Automatizar a integração e tratamento dos dados operacionais • Modelar e automatizar tabelas refinadas • Implementar monitoramento e alertas proativos • Publicar e validar as tabelas em ambiente produtivo • Documentar toda a estrutura técnica e funcional da plataforma • Realizar treinamentos e formalizar o handover técnico