We’re looking for a talented and experienced Senior Data Engineer to join our team and help design, build, and scale modern data platforms. In this role, you’ll lead the development of robust data pipelines, optimize data architecture, and ensure high-quality, reliable data flows across systems. You’ll collaborate closely with product managers, software engineers, analysts, and business stakeholders to translate complex requirements into scalable data solutions that power reporting, analytics, and decision-making. If you’re passionate about clean, efficient data models, resilient ETL/ELT processes, and building infrastructure that turns raw data into actionable insight, we’d love to hear from you. This position is a full-time role. We are 100% remote but candidates must reside and be authorized to work in Costa Rica. Responsibilities - Design and implement cloud-based data platforms, pipelines, and data hubs for client engagements - Support modernization and migration of legacy data systems to cloud-native architectures - Build and maintain high-quality, scalable data pipelines with strong observability and reliability - Combine data from multiple sources to create comprehensive, trusted data assets - Set up cloud compute and storage (AWS, Azure, SaaS/PaaS, SSO) based on project requirements - Design and implement centralized Data Hubs supporting AI/ML, KPI dashboards, SSO, and integrations across platforms (e.g., MarTech, eCommerce, EdTech, DXP, learning systems) - Develop reusable components for ingesting, normalizing, transforming, and serving data (DWH, reporting, dashboards, AI/ML use cases) - Implement lightweight, effective data modeling strategies focused on performance and maintainability - Ensure high availability, data quality, observability, governance, and cataloguing best practices Required - 10+ years of experience in data engineering, data platforms, BI engineering, and/or data architecture - Proven experience with end-to-end data management, including data governance, cataloguing, observability, and quality. - Advanced SQL expertise (query optimization, performance tuning, complex transformations). - Hands-on Azure Fabric experience - Strong SSIS and SSAS experience - Strong Power BI experience, including data modeling, report/dashboard development, and performance optimization - Experience designing and optimizing Data Lakes and enterprise data warehouses - Demonstrated leadership in legacy system modernization to cloud (Azure preferred) - Strong debugging and root-cause analysis skills - Experience with at least one major cloud (Azure strongly preferred; AWS/GCP acceptable) - Experience with Git and CI/CD best practices - Excellent communication and client-facing skills Nice To Have - Experience with AWS, Azure, or GCP (multi-cloud exposure a plus) - Experience with tools such as FiveTran, Snowflake, dbt, Google Analytics, Tableau - Experience designing and deploying solutions on AWS (Lambda, RDS, DMS, S3, Snowflake or similar cloud data warehouse) - Python experience building data pipelines, automation scripts, and AI/ML workflows, including integration with cloud services and data platforms. - Experience supporting AI/ML infrastructure and workflows - Exposure to Large Language Models (LLMs) - DevOps experience including Infrastructure as Code and deployment automation Benefits This is a full-time position with the following benefits: - Competitive Base Salary - Great work deserves great pay. Our salaries covers a 40-hour work week, and we also offer optional paid overtime for this position. - Optional Paid Overtime - At JBS, overtime is never required, but if you choose to work additional hours beyond 40 in a week, those hours are compensated at an overtime rate. The decision to take on extra work is entirely employee-driven; we respect your time and encourage a balance that works best for you. - Private Health Insurance – In addition to CCSS coverage, we provide private medical insurance to give you faster access to care and expanded provider options for you. - Generous PTO Policy – Take the time you need to rest and recharge. We provide paid vacation in addition to paid public holidays. - Fully remote - We’ve always been (and always will be) 100% remote All JBS roles are fully compliant with Costa Rican labor law, including but not limited to: - CCSS Enrollment (Caja Costarricense de Seguro Social). This ensures access to Costa Rica’s national healthcare system, disability coverage, and pension benefits. - Aguinaldo (13th Month Bonus) – Employees receive the legally required annual Aguinaldo bonus, paid in December.

We’re looking for a talented and experienced Senior Data Engineer to join our team and help design, build, and scale modern data platforms. In this role, you’ll lead the development of robust data pipelines, optimize data architecture, and ensure high-quality, reliable data flows across systems. You’ll collaborate closely with product managers, software engineers, analysts, and business stakeholders to translate complex requirements into scalable data solutions that power reporting, analytics, and decision-making. If you’re passionate about clean, efficient data models, resilient ETL/ELT processes, and building infrastructure that turns raw data into actionable insight, we’d love to hear from you. This position is a full-time role. We are 100% remote but candidates must reside and be authorized to work in the United States. Responsibilities - Design and implement cloud-based data platforms, pipelines, and data hubs for client engagements - Support modernization and migration of legacy data systems to cloud-native architectures - Build and maintain high-quality, scalable data pipelines with strong observability and reliability - Combine data from multiple sources to create comprehensive, trusted data assets - Set up cloud compute and storage (AWS, Azure, SaaS/PaaS, SSO) based on project requirements - Design and implement centralized Data Hubs supporting AI/ML, KPI dashboards, SSO, and integrations across platforms (e.g., MarTech, eCommerce, EdTech, DXP, learning systems) - Develop reusable components for ingesting, normalizing, transforming, and serving data (DWH, reporting, dashboards, AI/ML use cases) - Implement lightweight, effective data modeling strategies focused on performance and maintainability - Ensure high availability, data quality, observability, governance, and cataloguing best practices Required - 10+ years of experience in data engineering, data platforms, BI engineering, and/or data architecture - Proven experience with end-to-end data management, including data governance, cataloguing, observability, and quality. - Advanced SQL expertise (query optimization, performance tuning, complex transformations). - Hands-on Azure Fabric experience - Strong SSIS and SSAS experience - Strong Power BI experience, including data modeling, report/dashboard development, and performance optimization - Experience designing and optimizing Data Lakes and enterprise data warehouses - Demonstrated leadership in legacy system modernization to cloud (Azure preferred) - Strong debugging and root-cause analysis skills - Experience with at least one major cloud (Azure strongly preferred; AWS/GCP acceptable) - Experience with Git and CI/CD best practices - Excellent communication and client-facing skills Nice To Have - Experience with AWS, Azure, or GCP (multi-cloud exposure a plus) - Experience with tools such as FiveTran, Snowflake, dbt, Google Analytics, Tableau - Experience designing and deploying solutions on AWS (Lambda, RDS, DMS, S3, Snowflake or similar cloud data warehouse) - Python experience building data pipelines, automation scripts, and AI/ML workflows, including integration with cloud services and data platforms. - Experience supporting AI/ML infrastructure and workflows - Exposure to Large Language Models (LLMs) - DevOps experience including Infrastructure as Code and deployment automation Benefits This is a remote full-time W2 employee position with the following benefits: - Competitive Base Salary - Great work deserves great pay. We offer a base salary range between $120,000 - $140,000, commensurate with years of experience, technical expertise, and overall qualifications. This salary covers a standard 40-hour work week, and we strongly value maintaining a healthy work-life balance. - Optional Paid Overtime - At JBS, overtime is never required, but if you choose to work additional hours beyond 40 in a week, those hours are compensated at an overtime rate. The decision to take on extra work is entirely employee-driven; we respect your time and encourage a balance that works best for you. - Generous PTO policy - Take the time you need to rest, recharge, or travel the world - 401k with company match - Contribute to your 401(k), and we’ll match up to 4% - Comprehensive Health Coverage - Medical, dental, and vision plans for you and your family, with 90% or more of your deductible completely covered - Fully remote - We’ve always been (and always will be) 100% remote As an equal opportunity employer, JBS does not discriminate in hiring or terms and conditions of employment on the basis of any federal, state, or locally protected class. JBS only hires individuals authorized for employment in the United States on a W2 basis

Team Members are at the core of who we are; living our core values of making a difference, doing the right thing, making it easy, being caring, being friendly, nice, and respectful, and taking ownership. Perhaps Royal is the change you’re looking for. Royal Credit Union is looking for caring, energetic team members who want to create a positive impact in the lives of our Members. Is this you? If so, let us know by submitting an application! Are you passionate about transforming raw data into meaningful insights? Do you thrive in a collaborative, innovation‑driven environment? Become a Data Engineer at Royal Credit Union! In this role, you’ll help build our cloud‑based Business Intelligence platform, solve complex analytical challenges, and create data systems that empower teams across the organization. Why Royal? - Member and Community Focused: We are dedicated to making a positive impact on our Members and the communities we serve, going beyond financial services to enrich lives and foster growth. - Supportive Environment: Join a collaborative, values-driven workplace that is always evolving. We support each other and work together to achieve our goals. - Professional Growth: We offer numerous opportunities for training and advancement, helping you continuously develop and advance your skills. - Empowerment: We empower our team members to make decisions and drive initiatives that help our Members achieve their financial goals. Your ideas and contributions are valued and encouraged. - Community Involvement: Engage with your local community through various initiatives and events, making a tangible difference where you live and work. Be part of something bigger. What You’ll Do: The Data Engineer will work in a team that is building the Business Intelligence platform at Royal. This includes the use of various methods to analyze and transform raw data into useful cloud-based data systems. Involving increasingly complex level of data and statistical analysis in support of creating and shaping data systems, pipelines, and other business-related activities. Resolutions may require more in-depth quantitative analysis with non-routine solutions. Support line of business for all quantitative needs to include leading mid-size initiatives. Our Commitment To You: - Compensation: $99,600 - $131,900 (candidates with significant related experience may be higher. pay also depends on candidates location) - Benefits: Royal is proud to take care of our team members and their families! In addition to our comprehensive medical, dental, and vision insurance plans, Royal offers a 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! What’s Needed For This Position: - Bachelor’s Degree or the Equivalent in 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 experience, including knowledge of extensive data ecosystem - Must be bondable - Advanced data architecture and system design expertise, including experience working with multiple file structures (flat files, JSON, XML), 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, data management principles, and implementing cloud-based analytic solutions (AWS, Azure, etc.). - Strong data connectivity and integration capabilities, including working with APIs (REST/SOAP), ODBC/JDBC, HTTP webhooks, and overseeing data cleansing, standardization, and advanced analytic solution development. - Effective communication and collaboration abilities, including summarizing technical concepts for non‑technical audiences, working within Agile environments (Azure DevOps), using version control (Git, Kubernetes), and contributing to cross-departmental documentation and process improvement. - Exceptional problem‑solving and adaptability, with the ability to perform root‑cause analysis, handle ambiguity, juggle multiple projects, embrace change, and leverage technology solutions while respecting confidentiality and security standards. We’d Love To See: - Experienced in implementing Data and Advanced Analytic solutions, or related experience in the Cloud (AWS, Azure, etc.) - Experience implementing an end-to-end Cloud native platform for Datawarehouse (Snowflake, Databricks, Big Query, Redshift, etc.) - Experience with data connectivity methodologies such as APIs (Rest/Soap), ODBC/JDBC, HTTP web hooks, JSON, etc. - Intermediate experience with data management principles 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. Please note - Royal Credit Union reserves the right to determine remote status eligibility and the state we allow team members to work from. Training: - Prior to starting a normal work schedule, new Royal team members must attend Foundation Training at our Corporate Center in Eau Claire, WI from 9:00am - 4:30pm on Monday and Tuesday during their first week of employment. Out of town learners will be reimbursed costs related to travel and lodging. - Foundation Training covers fundamental information about Royal’s culture and core values which sets the stage for team members to be successful within our organization. Ready to make a positive impact? APPLY NOW if you are ready to take on this exciting challenge and become a part of the Royal Credit Union family! We will be communicating with you by email and/or text on the status of your application. Please monitor your email inbox and junk folder for status updates and additional instructions. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, age, protected veteran status or status as an individual with disability.

• Design and implement scalable cloud-native data architectures using Microsoft Fabric and Azure data services. • Define best practices for data governance, architecture standards, and platform scalability. • Build robust data models and data warehouse architectures to support analytics and AI workloads. • Design and develop high-performance ETL and ELT pipelines for large-scale data processing. • Build and maintain data pipelines using Python and SQL to process and transform complex datasets. • Ensure reliability, scalability, and performance optimization across data workflows. • Develop and manage data engineering workflows using Databricks, Spark, and Delta Lake. • Implement data ingestion frameworks and support large-scale data processing environments. • Optimize data pipelines for performance, reliability, and cost efficiency. • Design workflow orchestration using tools such as Airflow or Azure-native orchestration services. • Automate data processing pipelines and maintain operational reliability across systems. • Collaborate with machine learning teams to support LLM, NLP, and AI-driven data workflows. • Enable feature engineering and data pipelines that support advanced analytics and AI models. • Establish best practices for data architecture, pipeline management, documentation, and security. • Ensure compliance with enterprise data governance and quality standards.