• Design, implement, and operate production data platforms across Azure SQL, on premise SQL Server, Azure Storage, Microsoft Dataverse, and Microsoft Fabric or Power BI. • Build and maintain ingestion pipelines using SFTP file drops, APIs, CDC or SQL Log Shipping patterns, and Azure Data Factory or equivalent orchestration tools. • Design and evolve analytic data models using star, snowflake, Data Vault, or hybrid approaches. • Implement automated data quality checks, validations, and alerts across pipelines and semantic layers. • Implement practical data governance using Microsoft Purview or equivalent tooling. • Partner closely with DevOps to reduce manual processes and increase repeatability.

• Design and develop modern data engineering solutions — including data pipelines, lakehouse architectures, and analytics platforms — for the largest companies and organizations in Nordics. • Design, build, and maintain scalable data integration and transformation pipelines across cloud-native data platforms. • Apply data modeling and governance best practices to ensure reliable, scalable, and business-aligned analytics solutions. • Collaborate with customers and stakeholders to gather and translate requirements into technical solutions. • Optimize pipeline and platform performance to meet scalability and reliability demands. • Contribute to documentation and knowledge sharing within the team. • Work in agile teams, participating in planning, reviews, and continuous improvement. • Stay current with emerging data technologies and bring relevant innovations into your work.

Title: Data Engineer Location: USA Job Description: Let’s do great things, together! About Moda Founded in Oregon in 1955, Moda is proud to be a company of real people committed to quality. Today, like then, we’re focused on building a better future for healthcare. That starts by offering outstanding coverage to our members, compassionate support to our community and comprehensive benefits to our employees. It keeps going by connecting with neighbors to create healthy spaces and places, together. Moda values diversity and inclusion in our workplace. We aim to demonstrate our commitment to diversity through all our business practices and invite applications from candidates that share our commitment to this diversity. Our diverse experiences and perspectives help us become a stronger organization. Let’s be better together. Position Summary The Data Engineer role on the Data Science Team (DST) is responsible for designing, maintaining, and enhancing data integration pipelines that support the Enterprise Data Warehouse (EDW) and downstream analytics. This role supports the existing on premises data environment while actively contributing to cloud modernization initiatives, including the adoption of modern data transformation and cloud data warehouse technologies such as dbt and Snowflake. This is a FT WFH position. Pay Range $78,911.43 - $110,265.00 annually (depending on experience). *This role may be classified as hourly (non-exempt) depending on the applicant's location. Actual pay is based on qualifications. Applicants who do not exceed the minimum qualifications will only be eligible for the low end of the pay range. Please fill out an application on our company page, linked below, to be considered for this position. https://j.brt.mv/jb.do?reqGK=27777149&refresh=true Benefits: - Medical, Dental, Vision, Pharmacy, Life, & Disability - 401K- Matching - FSA - Employee Assistance Program - PTO and Company Paid Holidays Required Skills, Experience & Education: - 1 - 5 years of experience working with large datasets in relational databases and SQL-based data analytic platforms. Experience with SQL Server and modern SQL-based cloud data warehouses, e.g. Snowflake, BigQuery, Redshift, etc.) is preferred. - 1 - 5 years of hands-on SQL development experience, including writing complex queries, stored procedures, and performance tuning. - 1 - 5 years of practical experience developing and supporting data pipelines and transformations using SSIS, SQL Agent, Azure Data Factory, and/or Airflow. Exposure to modern cloud-based transformation tools such as dbt or similar is preferred. - Experience supporting on-premises data warehouse environments and contributing to future cloud modernization efforts, including assisting with migrations from on-premises SQL Server–based platforms to Snowflake or similar cloud technologies. - Solid understanding of data management principles, relational data structures, and data modeling, with the ability to apply best practices in both on-premises and modern SQL-based cloud data warehouses. - Demonstrated analytical skills and ability to contribute to data driven solutions that address real business problems, with guidance from senior engineers when needed. - Working knowledge of Agile development methodologies and participation in collaborative, team-based delivery models. - Exposure to DevOps practices using tools such as Azure DevOps (CI/CD, work item tracking, GIT version control, Pull Requests) is desirable. - Experience working with business intelligence and reporting tools such as SAS Enterprise Guide, Power BI or SSRS, including supporting downstream analytics and reporting users. - Familiarity with programming or scripting languages such as Python, R, or Java is a plus. - Experience with healthcare data is strongly preferred. - Bachelor’s degree in a related field or equivalent practical experience preferred. Primary Functions: - Design, develop, test, and maintain ETL/ELT pipelines that ingest data from multiple internal and external source systems into the Enterprise Data Warehouse (EDW). - Automate, maintain and enhance existing data pipelines to ensure reliability, performance, and scalability, while implementing incremental improvements as part of ongoing cloud modernization efforts. - Contribute to data platform modernization initiatives, including assisting with migrations to cloud-based infrastructure and adoption of modern data tools and practices. - Develop, implement, and support data quality checks, validation processes, and monitoring to ensure data accuracy and consistency. - Build and support modern, enterprise-grade data pipelines and models under the guidance of senior engineers to enable adoption of next-generation data architecture. - Collaborate with cross-functional teams to understand data and reporting requirements and provide ongoing support for data infrastructure needs. - Support the Data Science team by implementing and maintaining data solutions that enable advanced analytics and machine learning cases. - Participate collaboratively in Enterprise Data Warehousing, Business Intelligence, and other data management initiatives, including code reviews and documentation. - Perform other duties as assigned. Working Conditions: - Office environment with extensive close PC and keyboard use, constant sitting, and frequent phone communication. Must be able to navigate multiple computer screens. A reliable, high-speed, hard-wired internet connection required to support remote or hybrid work. Must be comfortable being on camera for virtual training and meetings. Work in excess of standard workweek, including evenings and occasional weekends, to meet business need. - Experience in healthcare systems is a plus; Facets experience preferred. Together, we can be more. We can be better. ​​​​​​ Moda Health seeks to allow equal employment opportunities for all qualified persons without regard to race, religion, color, age, sex, sexual orientation, national origin, marital status, disability, veteran status or any other status protected by law. This is applicable to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absences, compensation, and training. For more information regarding accommodations, please direct your questions

• You will be a part of the team accountable for design, model and development of whole GCP data ecosystem for one of our Client’s (Cloud Storage, Cloud Functions, BigQuery). • Involvement throughout the whole process starting with the gathering, analyzing, modelling, and documenting business/technical requirements will be needed. The role will include direct contact with clients. • Modelling the data from various sources and technologies. Troubleshooting and supporting the most complex and high impact problems, to deliver new features and functionalities. • Designing and optimizing data storage architectures, including data lakes, data warehouses, or distributed file systems. Implementing techniques like partitioning, compression, or indexing to optimize data storage and retrieval. Identifying and resolving bottlenecks, tuning queries, and implementing caching strategies to enhance data retrieval speed and overall system efficiency. • Identifying and resolving issues related to data processing, storage, or infrastructure. Monitoring system performance, identifying anomalies, and conducting root cause analysis to ensure smooth and uninterrupted data operations. • Train and mentor less experienced data engineers, providing guidance and knowledge transfer.