Role Description The Healthcare Data Engineer will be responsible for designing, developing, and maintaining data pipelines and systems that support healthcare data analytics and reporting. This role requires a deep understanding of healthcare data, including Electronic Health Records (EHR), Clinical Information Systems (CIS), and other healthcare data sources. The ideal candidate will have experience with Azure, data integration, and a strong background in data engineering. - Design, develop, and maintain scalable data pipelines and systems for healthcare data integration and analytics. - Collaborate with data scientists, analysts, and other stakeholders to understand data requirements and deliver solutions that meet business needs. - Ensure data quality and integrity by implementing data validation and cleansing processes. - Optimize data workflows for performance and scalability. - Develop and maintain documentation for data processes, architectures, and workflows. - Implement data governance and security best practices to ensure compliance with healthcare regulations (e.g., HIPAA). - Monitor and troubleshoot data pipeline issues to ensure timely and accurate data delivery. - Stay updated with the latest trends and technologies in data engineering and healthcare analytics. Qualifications - Bachelor's degree in Computer Science, Information Technology, Data Science, or a related field. A Master's degree is a plus. - 4+ years of experience in data engineering, with a focus on healthcare data. - Proficiency in SQL and experience with database technologies such as SQL Server, PostgreSQL, or similar. - Experience with cloud platforms, particularly Microsoft Azure, including Azure Data Factory, Azure SQL Database, and Azure Databricks. - Knowledge of healthcare data standards and formats, such as HL7, FHIR, ICD-10, and CPT. - Strong programming skills in languages such as Python, R, or Scala. - Experience with ETL tools and processes. - Familiarity with data visualization tools, such as Power BI or Tableau. - Excellent problem-solving skills and attention to detail. - Strong communication and collaboration skills. Requirements - Experience with big data technologies such as Hadoop, Spark, or Kafka. - Knowledge of machine learning and data science methodologies. - Experience working with Electronic Health Records (EHR) systems, such as Cerner or Epic. - Certification in Azure or other relevant technologies. Benefits - A values-driven workplace where people really matter. - Flexible work location. - Support for remote work/work from home. - Competitive salary, retirement savings program, and rewards program. - Comprehensive health, dental, vision, life and disability insurance plans and access to e-health care. - Paid vacation, maternity/parental leave, paid sick leave and paid Mariner MyLife days. - Unlimited training.

Role Description Zapata Technology is hiring a Software / Data Engineer to own and modernize a mission-critical data ecosystem. This is not a “run the pipeline” role — this is a build the next generation data platform role. You’ll take an environment currently powered by custom ASP.NET apps, Postgres stored procedures, and legacy VBA scripts and architect the transition to modern, scalable ETL and orchestration frameworks like Apache NiFi and Airflow. If you enjoy untangling complex data systems, designing clean pipelines, and turning “it works but no one knows how” into “it’s automated, documented, and scalable” — this role is for you. 100% Remote Job Functions - Own the design and evolution of our ETL and data pipeline architecture - Replace fragile VBA and ad-hoc scripts with robust, testable data workflows - Design high-performance Postgres data models, queries, and stored procedures - Build ingestion and transformation services using Python, ASP.NET, and SQL - Lead the migration from custom ETL processes to modern tools (NiFi, Airflow) - Create data pipelines that power analytics, reporting, and operational systems - Improve data quality, observability, and governance across the platform - Partner with stakeholders to translate messy requirements into clean data solutions - Document and automate everything so the system scales beyond any one person The Environment You’ll Help Build - Python-driven pipelines - Apache NiFi / Airflow orchestration - Clean Postgres architecture - AWS-based data infrastructure - Scalable, observable ETL workflows Qualifications - Strong experience building ETL/data pipelines without relying solely on ETL tools - Deep SQL and Postgres performance tuning experience - Experience writing data services in Python, C#, or ASP.NET - Experience modernizing legacy data environments - Comfort owning architecture decisions and working independently - Experience migrating systems to AWS - Familiarity with Spark, Databricks, or distributed processing is a plus - Shell scripting and automation experience - Experience working in Agile teams - 4+ years of software or data engineering experience - Strong SQL and database design background - Experience building and maintaining ETL processes Benefits - You get real ownership of architecture decisions - You are hired to modernize, not maintain - High impact, visible work that affects the entire organization - Freedom to introduce modern tooling and best practices - Remote flexibility with a team that values autonomy - A rare opportunity to rebuild a data platform the right way Position Type Full time position Clearance This position requires an active Secret clearance with the ability to obtain TS/SCI. Company Description Zapata Technology, Inc is an Equal Opportunity Employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability or protected veteran status. Zapata Technology, Inc. provides reasonable accommodation to applicants who are veterans or who have disabilities and are unable to fully use our company application system. If you need a reasonable accommodation for any part of the application and hiring process, please notify Christina Hall, EEO Coordinator at Zapata Technology. 706-955-4809

• Facilitate, guide, and influence the client and teams towards an effective architectural pattern and becoming an interface between business leadership, technology leadership and the delivery teams. • Designing of solution architecture on Google Cloud • Implementation of Proof of Concept (POC) and Minimal Viable Product (MVP) workloads. • Design a data platform that accounts for the implementation of: • Database objects • Data • Data Pipelines • Orchestration • Users and Security • Migration of workloads • Perform migration activities including: • Translation of DDL, Stored Procedures, and Queries into BigQuery and Cloud SQL supported (Postgres and MySQL) syntax • Executing data transfers using native Google Cloud and 3rd party tools • Setup and configuration of relative Google Cloud components through Infrastructure as Code (IaC) • Engage with customer teams as a Google Cloud expert to provide: • Education Workshops • Architectural Recommendations • Technology reviews and recommendations

• Design, implement, and maintain robust and scalable data pipelines using AWS, Azure, and containerization technologies. • Develop and maintain ETL/ELT processes to extract, transform, and load data from various sources into data warehouses and data lakes. • Collaborate with data scientists, analysts, and other engineers to ensure seamless data flow and availability across the organization. • Optimize data storage and retrieval performance by utilizing cloud services like AWS Redshift, Azure Synapse, or other relevant technologies. • Work with containerization tools like Docker and Kubernetes to ensure smooth deployment, scalability, and management of data pipelines. • Monitor, troubleshoot, and optimize data processing pipelines for performance, reliability, and cost-efficiency. • Automate manual data processing tasks and improve data quality by implementing data validation and monitoring systems. • Implement and maintain CI/CD pipelines for data workflow automation and deployment. • Ensure compliance with data governance, security, and privacy regulations across all data systems. • Participate in code reviews and ensure the use of best practices and documentation for data engineering solutions. • Stay up-to-date with the latest data engineering trends, cloud services, and technologies to continuously improve system performance and capabilities.