We are building the next generation of our enterprise data platform and are seeking a Cloud Data Engineer to architect, develop, and optimize large-scale, cloud-native data warehousing and ETL pipelines on AWS. You will be responsible for designing our data warehouses, implementing scalable AWS-based ingestion and transformation pipelines, and enabling high-quality analytics and BI across the organization. This role is ideal for someone with deep hands-on engineering expertise in cloud data ecosystems, data modeling, analytics enablement, and modern ETL patterns ESSENTIAL DUTIES AND RESPONSIBILITIES - Design and implement AWS-native ETL/ELT pipelines using services such as: - AWS Glue - AWS Lambda - Amazon MWAA / Apache Airflow - Step Functions - S# / Lake Formation - Architect and maintain data warehouses using Amazon Redshift (or Snowflake/Databricks on AWS). - Build robust data ingestion patterns including incremental loads, partitioning strategies, and schema evolution handling. - Ensure pipelines are secure, observable, cost‑efficient, and reliable in production environments. REQUIRED SKILLS AND ABILITIES - Strong understanding of data warehousing concepts and best practices - Expertise in SQL and query optimization for large-scale datasets - Proficiency in cloud data platforms (AWS preferred) and associated services (Glue, Lambda, Airflow, S3, etc.) - Strong programming skills (e.g., Python, C#, or similar) for ETL development and automation - Experience designing and implementing scalable ETL/ELT pipelines - Knowledge of modern data formats (Parquet, JSON, ORC) and file-based processing - Experience with data modeling (star/snowflake schemas, fact/dimension design) - Familiarity with data governance, lineage, and security in cloud environments - Experience integrating AI/LLM tools into engineering workflows is a plus - Strong written and verbal communication skills - Ability to manage multiple priorities and meet deadlines in a fast-paced environment KNOWLEDGE, EXPERIENCE, AND/OR EDUCATION REQUIREMENTS - Bachelor’s degree preferred but not required - - In lieu of a degree, equivalent experience in data engineering, computer science, or related field - 5–8 years of experience in data engineering or data warehousing - Hands-on experience with cloud data platforms (AWS strongly preferred) - Experience building and maintaining large-scale data pipelines and warehouses - Experience working with BI tools such as Tableau, Power BI, Quick Sight or similar - Experience with applied AI in data workflows is a plus Disclaimer: This job description is not intended to be an exhaustive list of all duties, responsibilities, or qualifications associated with the job. Management reserves the right to modify or reassign job duties as business needs evolve. #LI-RZ1 #LI-Remote Empyrean is an Equal Opportunity Employer: including disability and protected veteran status

• Conduct requirements analysis with the client • Design and optimize data architectures, including interfaces between systems • Support the implementation of a data warehouse architecture from concept through data validation • Take on lead responsibilities and manage own clients

• Build and scale high-throughput streaming pipelines • Design, implement, and operate pipelines ingesting 400M+ monthly MLS updates across 350+ integrations using Airflow, Spark Streaming, Kafka, and Iceberg • Model and deliver high-quality, production-grade real estate datasets • Develop and maintain datasets that power core product experiences • Strengthen data quality and observability • Implement and improve data quality checks, monitoring, and alerting • Leverage AI to improve data operations • Contribute to AI-driven tooling that helps triage, debug, and resolve data quality issues

Make a difference. Be happy. Grow your career. The Role ​​Nordic, repeat Best in KLAS IT Services Firm and solely serving the healthcare industry, strives to empower healthcare providers to leverage technology and to realize digital transformation. All Nordic staff embrace Nordic’s maxims and mission to serve our customers who care so well for us. Key Responsibilities - Designs, develops, optimizes, and maintains data architecture and pipelines that adhere to Extraction, Transformation, Loading (ETL) principles and best practices using Azure Databricks (PySpark)Works to identify business problems that can be solved and product features that can be enhanced by data engineering and analytics - Provides subject matter expertise as a product team member, for identification, estimation, and implementation of data solutions to business use cases - Collaborates with data analysts, key data consumers and application developers to optimize models and algorithms for data quality, security, and governance - Solicits, understands, and ensures compliance with data governance and data security requirements while creating and improving integrated and reusable data pipelines, to enable faster data access and improved time-to-solution for data and analytics initiatives - Leads engineering communities of practice (CoP) to expand influence and quality across the digital organization - Designs end to end DataOps and analytical workflows, including overall architecture, capabilities, platforms, tools, and governing processes - Mentors’ data team members to grow capabilities and mitigate product delivery risks Skills and Experience - Generally requires a Bachelor's degree in Information Systems, Engineering, Mathematics, Data Management, or other related degree and 8 years of related experience (required) - Master's degree Computer Science, Statistics, Applied mathematics, or information systems 6 and 6 years of related experience (preferred). - or 11 years of related experience and no degree. Minimum Years of Experience - 5 years’ experience in a data engineering or architecture role (required) 5 years’ experience designing, building, deploying, and troubleshooting data extract and load jobs (required) - 5+ years’ experience in building cloud data pipelines using Azure Databricks (PySpark) and Azure data factory - 3 years’ experience building DB objects, authoring, and troubleshooting SQL queries, stored procedures and ETL processes (required)5 years’ experience writing complex T-SQL queries, strong knowledge of DML, DDL, triggers, common table expressions (CTE), query tuning and performance optimization (required) - 3 years’ experience foundational data management practices, including: - Implement Delta Lake architectures, including medallion data models (bronze/silver/gold layers) - Demonstrated ability to design, build, manage and automate pipelines for data structures encompassing data transformation, data models, schemas, metadata, and workload management - Build reusable frameworks for metadata‑driven ingestion, orchestration, and error handling. - 3 years’ experience working with DevOps and continuous integration capabilities for version control, build automation, testing, and release management (e.g., Visual Studio, Git, Jenkins, Azure DevOps) (required) Other Knowledge, Skills and Abilities Required - License/Certification - Azure Data Engineer Associate (preferred) Additional Details - 1 year experience working with C#, PowerShell, Azure functions and logic apps, Azure Key Vault, .Net core, Azure PaaS (preferred) - 3 years’ experience Exposure to hybrid deployments, cloud and on premise, with demonstrated ability to work across multiple deployment environments, operating systems (preferred) Nordic is an equal opportunity employer. We are committed to creating an inclusive environment for all employees and applicants. We do not discriminate on the basis of race, color, religion, sex, national origin, age, disability, genetic information, marital or veteran status, or any other protected status under applicable federal, state, or local laws. We encourage individuals of all backgrounds to apply, including women, minorities, individuals with disabilities, and veterans.