• Set and own the technical and organizational north star for data engineering at AcuityMD—defining how we build the world’s most accurate and actionable model of healthcare reality. • Lead the design, implementation, and evolution of our core data platform, powering every aspect of our product and agentic experiences—from analytics and workflows to AI-driven insights. • Translate company and product strategy into clear data investments, and clearly articulate the customer value of those investments to engineering, product, and leadership partners. • Go deep when it matters: drive architectural decisions, review critical designs, debug hard problems, and coach the team through complex technical tradeoffs. • Build data systems that are constantly improving, reliable, and trusted—supporting massive scale, complex healthcare data, and customer-facing use cases where correctness truly matters. • Partner closely with product, data science, and engineering leaders to ensure tight feedback loops between data generation, modeling, and real-world customer outcomes. • Lead, mentor, and grow a high-impact team of data engineers, data scientists, and domain experts, setting a high bar for methodological and technical rigor, ownership, and velocity. • Establish strong—but pragmatic—standards for data quality, testing, observability, lineage, and governance, without slowing the team down. • Shape the culture of the data organization: how we plan, how we ship, how we review work, and how we learn from mistakes. • Stay close to the evolving state of modern data engineering and analytics engineering, bringing in new ideas when they meaningfully raise our ceiling.

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description As a key technical leader and team architect working in a fast-paced environment, you will drive the design, development, and optimization of scalable data ingestion pipelines within the Arine platform. Leveraging expert-level proficiency in Python and AWS, you will architect solutions that handle diverse file types and large-scale healthcare datasets. You will have a direct impact on building reusable, configurable tools set for handling data needs for the entire company. What You'll be Doing: - Act as the team architect by leading system design reviews, offering recommendations, conducting comprehensive peer reviews, and demonstrating expert-level proficiency in Python and AWS services. - Architect and implement scalable data ingestion pipelines that handle different file types into the Arine platform. - Develop reusable components that integrate into data pipelines to increase efficiency and reduce future implementation time. - Create configuration-driven, containerized toolsets that are easy to use and maintain across diverse engineering profiles. - Work collaboratively with cross-functional teams to meet data requirements through ETL components. - Design and maintain data transformation pipelines using DBT, including macros, incremental models, and DBT tests. - Implement incremental data ingestion strategies for large-scale healthcare datasets. - Build monitoring and alerting systems for data ingestion processes and overall pipeline health. - Apply software engineering best practices, including test-driven development and modular design, to data infrastructure. - Refactor and rebuild existing data ingestion processes to improve scalability and operational efficiency. - Work with containerization technologies (Docker, Kubernetes) to create portable and maintainable data solutions. - Identify and escalate inefficiencies within and across teams. - Provide technical guidance and mentorship to junior engineers, and promote best practices and coding standards. - Author and maintain high-quality technical documentation, and support junior engineers in doing the same. - Collaborate with the DE Manager to report on DE contractor performance issues. Qualifications - 10+ years working in data engineering, with a focus on large-scale data ingestion and infrastructure. - Deep expertise in Python and modern data engineering tools. - A track record of building automated, production-grade ETL processes using Python and dbt SQL. - Strong understanding of ETL/ELT frameworks and distributed data processing. - Hands-on proficiency with modern data technologies and comfort leveraging AI coding assistants to accelerate development, improve code quality, and enhance productivity. - Skilled in data processing, validation, cleaning, and debugging. - Strong capability integrating APIs for seamless data exchange between systems. - Proven ability to handle and process varied file types and formats, including healthcare standards such as HL7, 834, 837, and NCPDP. - Demonstrated success integrating and consolidating data from diverse source systems into a unified repository, including EHR and claims systems, via both file-based and API integrations. - Comfort working with large-scale datasets (10GB+). - Strong capability implementing incremental processing and change data capture (CDC) methodologies. - Extensive background designing scalable data architectures in AWS environments. - Solid grounding in software engineering principles, including test-driven development, loose coupling, single responsibility, and modular design. - Hands-on familiarity with containerization (Docker, Kubernetes) and building configuration-driven, maintainable systems. - Proven ability to build tools and systems that diverse engineering profiles can operate through configuration rather than code changes. - A passion for building new data infrastructure and continuously improving existing systems with robustness, maintainability, and operational excellence. - Familiarity with healthcare data and regulatory environments (HIPAA) as a plus. - Strong collaboration skills, with comfort partnering across technical and non-technical stakeholders. - Excellent written and verbal communication, with the ability to explain technical infrastructure concepts to diverse audiences. Requirements - Ability to pass a background check. - Must live in and be eligible to work in the United States. Benefits - Dynamic role with the opportunity to contribute to the company's growth and shape its future. - Unparalleled learning and growth prospects, collaborating closely with experienced Clinicians, Engineers, Software Architects, and Digital Health Entrepreneurs. - Salary range for this position is: $170,000-185,000/year. Remote Work Requirements - An established private work area that ensures information privacy. - A stable high-speed internet connection for remote work. - This role is remote, but you will be required to come to on-site meetings multiple times per year.

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description HSAG is seeking a Data Manager I to join the Data Science & Advanced Analytics (DSAA) division, focusing on managing claims and encounter data within a Microsoft SQL Server environment. This role emphasizes data integrity, compliance, and quality improvement in healthcare analytics. The Data Manager I position is a key contributor to healthcare data management projects, with a focus on claims and encounter data. Responsibilities include: - Supporting extraction, transformation, and loading (ETL) processes - Data validation and reporting in a Microsoft SQL Server environment - Developing and maintaining data dictionaries - Conducting audits - Collaborating with internal teams to ensure accurate data collection and reporting - Training team members on data management best practices - Ensuring compliance with health data regulations The Data Manager I will work with a wide array of healthcare data types, including but not limited to: - Survey - Case review - Medical and prescription drug claims and encounters - Eligibility - Demographic - Clinical - Electronic health record - Registry - Vital statistics - Operational Qualifications - Bachelor’s degree in computer science, computer information systems, or a quantitative discipline - At least three (3) years of experience with ETL processes in a Microsoft SQL Server environment - At least three (3) years of data warehousing experience - Excellent SQL programming skills - Experience gathering and refining requirements, interviewing business users to understand and document data requirements - Strong attention to detail, documenting business and technical requirements based on user interviews - Database testing experience - Experience with Microsoft SQL Server Requirements - Experience working with healthcare data - Proficient in Microsoft Word, Excel, and Access - Excellent verbal and written communication skills - Ability to handle several projects simultaneously and work with multiple teams Benefits - Formal internal training on an assortment of healthcare-related topics during the first year

• Develop and maintain scalable data pipelines and ETL processes. • Design, implement, and optimize existing data extraction and loading processes with adequate data engineering design patterns. • Lead data engineering reliability and observability, increasing analytics team awareness of the data flow processes before it becomes an issue. • Collaborate with backend and analytics engineers in a holistic data engineering process, loading data accordingly with the technical requirements. • Ensure data quality and consistency across various sources by implementing data validation and cleansing techniques. • Work with cloud-based data warehouses and analytics platforms to manage and store large datasets. • Monitor and troubleshoot data pipelines to ensure reliable and timely delivery of data. • Document data processes, workflows, and best practices to enhance team knowledge and efficiency. • Create dashboards as data products as internal